SQL is among the skills learned in a minute but takes years to master. We’ve crafted this step-by-step guide to not only strengthen your technical skills but also prepare you for tackling practical challenges in the industry with confidence.
In this article, we explore the top sklearn datasets for machine learning projects, including toy, real-world, and synthetic datasets, to help you practice and build models efficiently. Each dataset is detailed with its features, targets, and code example
Practicing SQL interview questions can reveal common mistakes that often trip up candidates during high-pressure technical interviews. To help you prepare and avoid these pitfalls, we've outlined the most frequent errors candidates make.
In this article, you will learn the difference between Python and SQL to help you decide which tool is best for your data needs. We’ll explore the strengths and roles of both languages to give you a better understanding.
Since you're exploring data engineering roles, we've compiled essential details to give you a clearer picture of what to expect in the role and how to effectively advance your career.
To help you get started, we have compiled 19 Python projects for beginners. In this list, we highlight the objectives of each and the skills you’ll learn by completing them.
In this article, we’ll go through the critical components of a data analyst resume without experience that have the potential to make or break your application.
In this guide, we’ll tell you what it takes to go from student to supply chain analyst. We’ll explain what a supply chain analyst does, the skills needed, the steps in this career path, and more.
To help you focus on your project and not worry about data quality, we’ve gathered the best websites with repositories for free data science datasets you can build a solid foundation on.
There are multiple facets to becoming a machine learning engineer and staying on top of the game, from having the necessary skills and educational background to earning the needed certifications and practicing interviews. Before we dive deep into how to b
This article discusses whether statistics is challenging for data science students. Additionally, we explain why this is the case and the approaches you can take to more easily acquire and understand the statistical knowledge you need as a data scientist.
This article takes you through 11 of the best machine learning projects for beginners today. These projects offer a solid introduction to different concepts, help hone your problem-solving skills, and get you working on real-life applications of machine l
In this article, we’ve explored the fundamentals of data engineering master’s programs and the career advantages you can expect by enrolling in one.
We’ve selected these 17 specific tools because they cover core needs in data science, from data visualization and statistical analysis to machine learning and data cleaning.
You're in the right place to discover the steps involved in becoming a skilled data analyst and to learn how long it might take to reach your goal.
Despite the challenges and what we believe was a “pretty intensive interview,” Keerthan’s strategic preparation paid off, earning him the desired position at Intuit and a 20% salary increase.
In a surprising and significant shift, job listings from FAANG companies (Facebook, Amazon, Apple, Netflix, and Google) grew by a remarkable 69.1% from September to October 2024.
Since partnering with Interview Query in 2022, the platform has provided tailored learning paths, peer-to-peer mock interviews, and an extensive library of technical questions, helping students strengthen their skills in SQL, coding, and data analysis.
In this article, we've curated a list of 20 datasets, ranging from beginner to advanced, to help you kick-start your projects.
In this article, we dive into the journey of an early-career data scientist and how you can go from student to associate data scientist.
With data engineering skills ranging from knowledge in programming languages to building systems that manage big sets of data, data engineering is an in-demand career and is essential to many companies and corporations.
This article highlights nine entry-level SQL jobs that may be a good fit for you. We’ll discuss what these SQL jobs entail, possible salaries, and additional skills you’ll need to excel in these roles.
His career kicked off at Capital One, where he gained invaluable experience in data migration and automation. As his knowledge and skills grew, so did his ambition—leading him to land a position at Amazon.
This month's job market report reveals notable hiring trends and company dynamics shifts.
As interviews increasingly move online, the whole concept of interviewing has changed over the past couple of years, and you have probably felt this change as well.
This week, we caught up with Hanna Lee, a recent USF graduate who started in finance before deciding to become a data practitioner.
A meticulously crafted portfolio is essential for aspiring data analysts, especially when your experience alone isn't enough to make a strong impression.
In August 2024, the data science job market experienced significant changes, highlighting a dynamic and evolving landscape.
Fraud analysts use data analysis and investigative techniques to identify and prevent rogue activities. As someone applying for a fraud analyst role, you’ve come to the right place to catch a glimpse of questions that can be expected in its interview.
In this article, we’ll explore the entry-level data science jobs in 2024 that you can secure without extensive experience or a decorated resume.
August 2024 began with a stock market scare that quickly bounced back. Trends in August data science job market give a promising outlook.
Understanding the difference between a data scientist vs data engineer is key if you’re considering a data-centric career. In this article, we’ll explain the difference between the two, the responsibilities of each expert, salaries, skills, and more to he
To reinforce your preparedness for the upcoming data science interview, we’ve compiled a list of data science coding interview questions in this article that you’ll find challenging and useful.
Meet Hoda, a dynamic data scientist who went from studying chemical engineering in Iran to thriving in the US tech industry.
In this article, we’ll go through how to use GROUP BY in SQL and address some real-world questions you might encounter in upcoming interviews.
In this article, learn what a data science mentor is and how they can help with your job search, offering guidance and support to advance your career in data.
This guide will help you navigate the hiring process to find the ideal software engineer, ensuring your team is productive, innovative, and thriving in the long run.
This article explains how you can use the SQL PARTITION BY clause to separate records and perform operations on them. We’ll show which functions can be paired with this clause and have included examples to help you understand how this clause is applied.
As the bedrock of relational databases, tables are fundamental in SQL. Deviating from our standard article, we’ll discuss a unique table called the SQL temp table, which exists only to be dropped.
Learn how Nathan Fritter, now a Senior Data Engineer at Capital One, successfully navigated the competitive field of data science using strategic networking, leveraging platforms like hired.com, and more.
The 2024 Data Science Report examines the evolving job market, exploring tech layoffs, post-COVID interview changes, and the impact of AI on the industry. It provides actionable insights for data scientists and engineers navigating these shifts.
This article explains the need for hiring data scientists today and where to find good candidates. We also look at how to recruit them, write job descriptions that attract the right applicants, interview prospective data scientists, and assess candidates.
If you're searching for a comprehensive guide to MySQL interview questions, then you've come to the right place. This page is tailored specifically for you. Click here to dive deep into the subject and master everything you need to know about MySQL interv
As you go through this PostgreSQL interview questions guide, you'll learn about all the possible questions and tips that hiring managers might ask during your interview. Read all about it here!
Machine learning is one of the most valuable skills that a data science professional can have in 2024. In this article, we'll provide you with the top machine learning case studies to look into.
Uncover the factors in data science that contribute to its appeal, including job market demand, earning potential, and the evolving landscape of data-driven industries.
This article will cover how to land a data science internship and share a few tips to effectively implement the strategies, together with what to expect as a data science intern.
If you're struggling to understand how hard it is to get a Google internship, this article is what you need. We've prepared the coherent steps necessary for you to land an internship at Google!
Read through this list of the highest-paying data science jobs. From roles such as Data Scientist to AI Architect, we've covered everything here!
If you're looking to know more about the top 27 data science companies right now, read through this article as we dive deep into the most notable ones you can consider applying to!
Familiarize yourself with the responsibilities and skills required for a data analyst role. This includes proficiency in data analysis tools like Python, SQL, or Excel, as well as understanding statistical concepts.
In this article, we'll discuss optimization strategies that can help mitigate issues. But first, let's understand the common challenges in optimizing SQL queries with multiple JOINs.
When approaching a business analytics interview, it’s imperative to recognize that your responsibilities will include understanding the business, identifying requirements, communicating, and making presentations and managing. With that, we’ve compiled the
This week, we've talked with Muhammad Imran Haider, and explored how he transitioned from doing financial analysis for commercial projects to practicing data science at Credit Expert.
We compiled 29 of the best artificial intelligence project ideas you can work on this year. We made sure there’s something for everyone on our list, whether you’re a beginner just dipping your toes in, a seasoned pro looking for a challenge, or somewhere
In this success story, we’ll explore how Dania transitioned from working in HR to attending OSU's data science program, and ultimately being hired for her very first data science position.
If you are currently exploring product analytics for the first time, or looking to improve your understanding, then this guide is for you.
Data analysts still hold some of the most in-demand qualifications in the job market in 2024. Many employers are hiring for this position, but some have more to offer.
After graduation, she worked as an Actuarial Analyst for almost four years. She then turned to Interview Query when she needed to prepare for her career change, and within three months she had two solid offers.
We caught up with the UCLA Director of Career Services, Larry Braman, to understand where MSBA students were experiencing challenges in 2021, and how Interview Query has filled the gap since then.
Simran Singh is a recent graduate of the University of Minnesota with a Master’s in Business Analytics. She took the time to talk more about her background and job h
Data scientists and computer scientists are two of the most in-demand experts right now, and choosing between the two careers can be hard.
In this article, we have curated an extensive list of Python projects perfect for enhancing your resume and demonstrating your skills to future employers.
Data scientist Alex Dang used Interview Query to keep his skills and knowledge fresh in between jobs. After facing a layoff from a rideshare company, he found himself in the competitive pool of candidates for his next opportunity in the industry.
If you’re searching for a comprehensive guide to acing an analytics manager interview, you’ve come to the right place.
Overall, data science listings remain below historic levels, but that has allowed FAANG to jump ahead in the share of total listings!
We’ve compiled the top 13 SQL scenario-based interview questions you can practice to pinpoint your skill level and improve. The problems and solutions are well-explained to assist you in understanding how you can approach similar questions in an actual in
In this article, we explore the significance and application of the Multiple CASE WHEN statement in SQL, along with some examples that you might encounter in a technical interview.
In this article, we will explore an important application of SQL JOINs, namely: SQL JOIN on multiple columns.
In this article, we’ll briefly touch upon the SUM() and CASE() functions, some common use cases, and how the two functions can be nested.
This week we caught up with Chandini Ramesh, who has held product analytics roles at Primer AI and Gloss Genius while attending graduate school at Georgetown University.
Overall, data science listings are in a holding position, with the exception of FAANG capturing a growing share of total postings and Business Intelligence taking off since the summer!
Many data engineers today have a robust portfolio of projects. Not only are these projects proof of strong technical experience, but they also showcase problem-solving abilities, creativity, and an aptitude for translating complex data needs into scalable
Today, we're taking a closer look at the UW MSDS program, including admissions, academic requirements, and fresh perspectives from UW graduates.
In this article, we’ll go through the most commonly asked linear regression interview questions, as well as a few tips to help you crack them.
In this article, we're discussing customer churn. We've scoured the internet for different kinds of customer churn datasets to highlight our favorites in order of difficulty.
In this article, we'll dive into interview questions you can use to prepare for an interview for the marketing analyst role.
Data analysts clean, analyze, interpret, and present data in order to gather business insights, drive business decisions, or create explanatory reports on observed phenomena. This role clearly encompasses a broad array of responsibilities, and raises the
This week we've caught up with Owen, who joined Intuit after completing his Bachelors in Data Science at UCSD in 2020 and followed an unconventional path.
In this article, we'll explore what a master's in data engineering is and whether it's worth investing in.
In this blog, we look at the differences between the data analytics and data engineering roles, as well as the implications of a transition from one role to another.
In this article, we'll dive into an overview of the position, similar analyst roles in the industry, and some supply chain analyst interview questions you can use to prepare for the role.
Discover an in-depth exploration of SQL LEFT JOIN, detailing its syntax, applications, and best practices to efficiently combine multiple rows from different tables.
From July to August of this year, almost all data science positions saw month-over-month increases. Data scientist positions saw the highest gains, with a 25% increase in job openings.
In this module, we cover the two key elements for acing a business analytics interview: understanding the business analyst role deeply and being well-prepared with the necessary tools and skills.
Dive into the 2023 journey of a fresh grad's rise in data science, from interview prep to landing a role at SoFi, plus insider tips for budding data scientists!
In this article, we'll dive into an overview of the position, the differences between certain types of analysts, and some pricing analyst interview questions you can use to prepare for the role.
In this article, we’ll examine the effects this tech is having in the broader job market, what it can and can’t do in data science, and whether this technology can actually replace data science in the near future.
In this article, we’ll take you through the steps you can follow to become a data analyst without a degree. We’ll explore what data analysts do, the skills they should possess, available resources to learn data analytics, and how to make up for the lack o
We spoke with almost two dozen Master’s graduates across Business Analytics and Data Science in the U.S., as well as gathering data from Glassdoor, Indeed, and LinkedIn to answer questions on how the current data science and analytics market is shaping up
In this article, we will delve into interview questions often faced by candidates for data analyst internships. Get ready to expand your knowledge on the usual topics covered, expectations from employers, and real-life interview questions.
At Interview Query, we love talking to our success stories. This week I talked to Jennetta who recently joined Attain as a data scientist. I asked her about her interviewing experience, how tough it was to get a job during the current pandemic, and advice
Today, I wrote up my interview with Jerry, a former data science bootcamp and master's graduate who went through a ton of interviews before landing his current job as a machine learning engineer
Explore other options and discuss why VLOOKUP isn’t possible or even a necessity in SQL
In this article, we'll compare the services and resources offered by Interview Query vs. DataLemur, two data interview preparation platforms.
In this article, you’ll learn everything you need to know about the role of a supply chain analyst, as well as the required skills to perform the role successfully, the career outlook, and the main industries hiring supply chain analysts.
Hedge fund data scientists specialize in data analysis, machine learning, and statistical modeling to make informed decisions.
SQL analytic functions, also known as window functions, are powerful features that perform calculations across rows in a result set, allowing for advanced data analysis and aggregation within queries.
Here’s what most prospective quants mistake for when preparing their first quant interview: they prepare for the wrong concepts.
Explore various aspects of conditional joins, including variations and advanced techniques.
The only guide you need for data architect interview process and technical interview questions.
In this article, we will explore syntax, usage, real-world examples, and advanced techniques of SQL's COUNT CASE WHEN statement and help you start using it in your queries.
mong the many techniques available, the weighted average is a powerful tool for deriving valuable insights from numerical data. But how exactly can we calculate the weighted average using SQL?
Explore different techniques and methods for calculating cumulative sums, enabling you to apply these queries confidently in your own projects.
This SQL cheat sheet for interview success is designed to help you ace any SQL problems you’ll face during your interview. It contains a comprehensive yet concise overview of SQL commands, techniques, and concepts with easy-to-understand examples and summ
The interview for a data engineering manager will be a mix of technical questions and behavioral approaches, focusing on a candidate’s people leadership and engineering management experience.
Discover your data analyst persona with this fun quiz!
Dhiraj offered insights into the difference between interviews for data scientist and manager-level roles, tips for interviewing success, and how you can turn a data science internship into a full-time job.
An analytical framework is a structure that helps us make sense of data in an organized way.
We spoke with Asef Wafa, a former Microsoft analyst, who landed a job at Google during the height of the December employment cuts.
Job openings in data science grew 11% monthly and 13% yearly across the board. We analyzed the data science job market to understand current trends.
Data science job openings are shifting to traditional industries in 2023. Data analytics is peaking as a specialty. We broke down the data science job market across industries, companies, and positions to understand the current trends.
Data science job openings grew 13% monthly but plummeted for FAANG. Healthcare, Retail, and Banking industries still actively hire data scientists. The shift toward data analytics continues in 2023.
We interviewed our coach, Jitesh Soni, who is passionate about sharing his knowledge, and we are delighted to learn more from his industry insights and tips to help you land your next dream job at a top company.
Ultimately, this pilot program of LMU – which was introduced out-of-pocket by the professor– presented Interview Query with the opportunity to learn how our courses, take-home challenges, and interview questions can be integrated into college courses.
Interview Query helped me understand differences in interview styles and personalize my interview prep for each company.
We’ll take you through our curated 14 SQL project ideas. These projects are divided into three groups based on difficulty.
There are two main things to consider when evaluating how much money you’ll make when you accept a tech job offer.
Today, we're taking a closer look at UIUC's MCS-DS program in order to get an overview of the program, admissions and academic requirements, and the perspective of a UIUC graduate, who now works in the San Francisco Bay Area in data science.
CASE WHEN` allows data scientists to create a pseudo if…else statement in SQL. We introduce the concept of MAX CASE WHEN dealing with data in SQL, finding use cases, and learning related concepts.
We looked at data science job posting data over the last 18 months and noticed there’s been a 26% drop YOY from October 2021 to October 2022 in the number of data scientist job openings.
This article will help you prepare for your next interview by covering the top 15 commonly asked deep-learning interview questions, covering the basics and beyond.
This article aims to provide an overview, outline the roles, and list essential data modeling interview questions and answers to prepare candidates for their interviews.
A professional degree is often a requirement for data science jobs, and this demand has resulted in a growing number of universities offering data science master's degrees and MBAs in business analytics/data analytics.
I came from an international background and grew up in three different countries. But as you can imagine, it wasn’t the most analytical or quantitatively rigorous major you could have, and preparations for a data science interview were challenging.
Although Google's search algorithm involves more than fuzzy matching SQL, this matching technique is an integral part of making your search experience seamless and relevant.
This list contains the top 27 Pandas interview questions, sorted based on their difficulty.
In this article, we’ll discuss some of the mathematical background behind the language, how to measure your skill level, and more SQL resources to check out.
Typically, a business analyst's SQL interview questions are designed to quickly assess your ability to pull metrics and process data with SQL.
Interviews for customer analyst roles typically include one or more customer analytics case studies.
Meet our AI and neuroscience expert coach with professional experience in natural language processing working previously on Alexa AI at Amazon.
E-commerce case studies are applicable to interviews for a variety of roles including marketing analytics, business intelligence, data science, and any type of strategic role that relates to attracting and retaining customers for an online brand.
Data science take-home challenges are a common type of assessment used in data science interviews, and they sometimes take the place of the technical screen.
For job positions requiring a lot of scientific calculations, matrix observations, financial, and deep learning analysis, NumPy interview questions will almost always come up. With this, this article serves as a guide for the top 19 NumPy interview questi
Some of the most common ways fintech companies use machine learning include fraud detection, risk analysis, and stock predictions. Fintech machine learning projects are the best way to gain hands-on experience.
You can create data visualization projects using data visualization datasets and assessing which technique to use to present them properly.
We can drill this down all we want, but at the end of the day, I I think maybe the phrase the hiring process is broken is prevalent for a reason
We share a complete guide into how it’s possible and what it takes to become a data scientist out of new grad
Completing a sports analytics project is one of the best ways to gain recognition and hands-on experience working with sports data and analysis. We've compiled some of the best sports analytics projects and datasets to help you practice.
Here are 10 Music Machine Learning projects with different levels of difficulty to familiarize you with the field.
Marketing analytics interview questions are a combination of definition-based and scenario-based case study questions.
We’ll define each field of software engineering and machine learning according to its traditional boundaries, identify key differences between them, and then finally look at the places where the two fields intersect and overlap.
These Data Science programs offer a unique variety of training and work experiences in diverse specialties that might be otherwise unavailable to new graduates trying to transition into full-time data science (and adjacent) positions.
Interested in learning and applying the skills that will land you a data science job in the new Supply Chain 4.0? Here are 12 Supply chain projects and datasets to help you start.
Should you grind questions on Leetcode or HackerRank? Should you do peer-to-peer interviews on Pramp? We’ve looked at the competition for preparing you for your data science interview and here’s how they stack up
Becoming a data science product manager requires a balance of technical knowledge, product management skills, and business acumen.
Don't know the difference between GROUP BY and WHERE? Here is Interview Query's one-all-end-all guide to Basic SQL Questions, designed to make your interview practice so much easier.
Is it worth it to switch careers from finance to data science? In this short guide, we will cover skill gaps, skill overlap, and finance-to-data-science salary comparison.
For non-US citizens, landing a dream data science job in Silicon Valley starts with visa sponsorship. Yet, for those without a US passport or green card, getting visa sponsorship is a complicated process.
A/B testing and statistics interview questions are usually asked in tandem in interviews, as statistics are heavily utilized in experiment design. This guide walks you through the top 49 commonly asked questions in this field, together with tips on how to
Mathematics plays an integral role in data science. We look at what math you need and how math is applied in data science and machine learning jobs.
Master's degrees in data science and adjacent fields seem to be all the rage lately...are they really the key to getting a job as a data scientist?
To help answer the question, we took a closer look at salaries for data scientists and statistics PhDs, as well as some of the pros and cons of pursuing a PhD for your data science career.
You might find yourself working on a data science take-home assignment in a zipped file with a requirements pdf that’s ten pages long as you are applying for a data scientist role. This guide offers you the six steps to ace these challenges!
This article covers the 11 best data engineering books, which you should have a copy of on your desk. We've covered a range of topics, including AWS, data cleaning, and Python books.
The product data science interview is meant to test your ability to understand how to build products.
The data science career path from junior to senior data scientist varies greatly in skill level, responsibilities, daily tasks, and everyone’s favorite topic– total compensation.
Curious about how much data scientists are making? Obviously, this is a huge– and typically taboo– question to ask just anyone, so in the spirit of full transparency, I’ll be telling you how much I’ve made in all of my data science positions ever since I
Whether you’re putting together a data science project to land a job or just want to brush up on your SQL or data analyst skills, we’ve selected some of our favorite sources of free data and useful datasets you can use for your next project.
Data science coaching is an increasingly popular strategy to help new and early-career data scientists land jobs.
Due to restrictive data collection methods and ethical concerns, developing a machine learning project involving the healthcare industry is too intimidating and challenging for many developers.
Data science interview books typically include insights into the conduction of interviews and have practice interview questions (with solutions), interviewing strategies, and tips.
Practicing image recognition machine learning projects is important for any aspiring data scientist.
This article will go through the fifteen best and most straightforward data science projects for marketing analytics to help you practice your skills.
Today, we’ll explore what is a fraud analyst, the required skills and education, and other essential information you'll need to dive into the field.
An overview of the processes involved in starting a data analytics project can be integral for tracking your progress without focusing too much on tasks that don't matter.
Are you interested in participating in the data-driven development of the real estate industry? Do you want to discover patterns in the real estate market? Here are ten awesome real estate machine learning projects to get you started.
Database design interview questions are often framed as hypothetical case studies or SQL coding questions.
Meta data scientists, analysts, and engineers are all asked SQL interview questions, more than the average technical interview. That's why it's extremely important to prepare for the SQL section of the Meta technical screen. To help you, we've prepared so
Growth in data science interviews plateaued in 2020. Data science interviews only grew by 10% after previously growing by 80% year over year.
This article will help you get through the Top 13 Amazon SQL interview questions, using your skills for one of the most highly sought-after FAANG companies.
We cover what you need to know, how SQL questions align to various Google roles, and SQL practice problems you can use to prep.
Data engineering is the fastest-growing job in the field. Interviews for data engineers increased 40% year-over-year, while data science interviews grew just 10%. In other words, the job outlook couldn’t be better.
Decision science and data science often get mistaken for one another. Both fields require many of the same skills, and there are similarities in how they approach analysis.
As data scientists, good data is something we define as raw, uncompromised, and observed in their natural state-- this is where social media datasets come into play.
This article provides an overview of Python data engineer interview questions.
These operational analytics interview questions require in-depth answers, and they are designed to see how you develop a data-driven solution to a potential BizOps problem.
Marketing Analytics Case study questions in interviews are scenario-based questions that mirror the day-to-day work of analysts.
Typically, ETL interview questions encompass a wide range of topics including, but not limited to, ETL testing, SQL, ETL coding (typically Python), and even system design.
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Business intelligence case studies are the most difficult part of business intelligence interviews, but using frameworks and understanding how they are graded can help you to prepare for your next BI case study interview.
Project-based behavioral questions are some of the most common inquiries you will receive during a data science interview.
The statistics and probability interview questions for quants and traders are framed as quantitative problems and ask interviewees to make calculations based on the provided information.
SQL data science interview questions mimic the work that data scientists actually perform. These questions ask candidates to pull metrics, aggregate data, and conduct analysis. In the majority of interviews, you will be required to write out or whiteboard
Here's an updated Interview Query FAQ and common issues.
Dive into the definitive 2024 guide covering 60+ Excel data analyst interview questions, from basic to challenging, and ace your next interview.
To excel in case study interviews for data science, practice is crucial. It will enable you to develop strategies for approaching case studies, asking the right questions to your interviewer, and providing responses that showcase your skills while adherin
Python interview questions feature prominently in data science technical interviews. You will likely be asked questions covering key Python coding concepts during a typical interview.
See 37 sample interview questions for product analysts. You can expect plenty of data analytics questions - namely SQL writing and statistics - as well as business/product sense questions.
Business intelligence professionals are tasked with identifying insights from streams of complex business data, which help the company stay more competitive, increase profitability, or solve specific business problems.
To answer probability interview questions, you need a strong basis in probability theory, and therefore it is recommended to brush up on it during your interview prep.
Data science behavioral interview questions are asked to gather specific information about your skills and experiences in terms of technical communication, job performance, cultural fit, adaptability, and technical competency.
Let’s take a closer look at how to use the OUTER JOIN.
This business intelligence career guide provides an overview of the field, an introduction to different BI job titles, and offers tips for breaking into business intelligence careers.
If you're preparing for a product analyst interview, you've come to the right place. In this article, we’ll cover everything you need to know about the role and answer essential questions about the field of product analysis.
Learn how to present data science projects in interviews, classes or on-the-job, including tips for aligning to your audience and what information to include.
We’ve compiled a list of the most common types of Data Science Manager interview questions, with examples for each.
To help us determine what you need to become a data scientist, Interview Query analyzed the profiles of more than 15,000 FAANG and start-up professionals on LinkedIn to see what the most common paths to becoming a data scientist are.
In this article, we’ve curated the best data science job boards that show fresh opportunities and will help you keep your finger on the pulse of the entire job market.
To help you study, we’re going to run through the Top 110 data science interview questions. All of these are real questions asked in data science interviews at companies like Facebook, Google, Amazon, and more.
Practicing sentiment analysis in a data science project can be exciting and fulfilling for both NLP beginners and experts. This article will suggest 12 sentiment analysis project ideas and datasets that you can work on regardless of your NLP-knowledge lev
Learn how to build an original data science project from scratch, including ideas for formulating a hypothesis and tips for sourcing data.
Interview Query founder Jay Feng counts down ways to build passive income streams with data science. if you’re motivated and have the time and resources to invest, you can explore these ways to generate passive income with data science.
Meta's (Facebook) data science intern program is one of the most competitive. Therefore, to land the job, you have to nail the interview and have the right skills.
Machine learning’s applications range from simple linear regression to image generation. This very complexity means that landing a role in machine learning requires more than a stellar resume; you need good machine learning projects and a portfolio.
Due to the great demand for data analytics across businesses and industries, business analytics professionals generally command a generous salary, especially with an advanced degree in relevant fields.
This article delves into various project ideas employing different regression analyses and the datasets you can use for implementation. These projects are suitable for those who are studying machine learning or preparing for job interviews, as well as for
Dive into the 2024 guide highlighting the top 20 classification datasets for machine learning. From beginner to advanced, embark on an exciting project journey!
If you feel you need a laugh, here’s some data science memes for some comic relief to make your job a little more fun.
Both platforms were built to help developers navigate tech interview preparations. However, neither platform was specifically designed and built for data science practitioners.
Data science projects are an incredible learning tool for practicing new skills and deepening your expertise. Whether you want to master data analytics or need to brush up on machine learning fundamentals, a data science project is one of the best ways to
There’s an endless array of ways in which Python can be used in data science, from building chatbots to detecting fraud. We’ve highlighted 18 great Python projects, ranging from beginning data science projects to more advanced projects and datasets.
Master’s in health informatics programs equip graduates with the niche training required to excel in various roles within this dynamic and lucrative industry. Professionals in this field earn competitive pay for their specialized skills.
Every company has questions related to their pricing: How should products be priced? How does pricing affect customer purchasing behavior? How will prices impact sales and revenue forecasts?
A master’s in data analytics requires a significant commitment of time and money, and that can leave you wondering: Is a master’s in data analytics worth it? We took a closer look at the pros, cons, and salary data to help you determine if a master’s in d
For those interested in becoming marketing analysts, we took a closer look at what is a marketing analyst, their key job responsibilities, job outlook and salary expectations, and what credentials you need.
The most apparent reason to consider a PhD in mathematics is the salary. For private industry jobs, math PhDs earn high starting wages.
Data analytics projects help you build your portfolio and land interviews. However, it’s not enough to just do an interesting analytics project. You also have to market your project to ensure it gets found.
This DoorDash case study guide provides everything you need to prepare! We have tips, a video overview, and sample DoorDash analytics case study questions.
Data scientists are particularly concerned about work-life balance in their field as the job is often described as demanding, especially since most of the time they are in front of a computer analyzing data and programming.
Learn more about the new feature Performance Score and our data science skills test, Challenges.
Follow these steps on how to prepare for the data science interview as it will help you study more effectively, build your confidence, and help you simulate the interview process.
Data science consultants possess a unique blend of technical expertise in data science and a deep understanding of business strategy, prompting them to receive a generous pay from top companies.
PhD in economics offers some of the highest starting salaries of any field. PhD in economics offers some of the highest starting salaries of any field.
A Master's in degree in data science results in a significant salary bump and increase career earnings.
Prepare for computer vision interview questions and learn what to expect in machine learning interviews.
See how companies like Scale use operational efficiency to label 1M data points per week.
A Ph.D. in data science doesn’t just offer a bump in salary; it’s increasingly becoming a required credential for the industry’s most prized jobs.
Explore some of the ways data science is used in cryptocurrency, from two data scientists working at crypto exchanges.
Given the demand for practical skills in data science, many data professionals are choosing between data science master’s programs and bootcamps to strengthen their qualifications.
This guide features an overview of what types of data visualization interview questions you can expect, as well as visualization practice questions.
We’ve put together this guide, which features everything you need to know about how to prepare for a data engineering interview.
This data engineering SQL questions guide provides an overview of the types of the SQL data engineer interview questions you might face to help you prepare for your interview.
This interview prep guide offers direction, covering what to study, how to study, and what you can do to prepare for a data analyst interview.
The title Machine Learning Scientist gets thrown around a lot, and it’s often confused with Data Scientist, but anyone who specializes in machine learning knows there’s a clear difference.
Learn more about data analyst career opportunities, including job outlook for data analysts, different roles and more.
See and learn sample machine learning algorithm interview questions that are commonly asked in data science interviews.
Python machine learning questions test your machine learning algorithmic coding ability and ask you to perform tasks like using pandas, writing machine learning algorithms from scratch, or answering basic Python questions related to machine learning. Th
Many machine learning interview questions are theory-based, testing your ability to apply ML concepts to business goals. This guide covers the top 67 machine learning interview questions, with tips to help you ace them!
Master your data engineer interview with our comprehensive guide, covering everything from SQL, Python, ETL, to behavioral questions and real-world case studies!
A data science skills test offers insight into your performance. For candidates, a well-calibrated skills test provides a score of where they stand compared to other data science professionals (similar to SAT percentiles).
SQL Interview Questions are commonly asked on every data analyst interviews. These interview questions aim to quickly evaluate your ability to extract metrics and work with data using SQL.
Most SQL interview questions are straightforward, but SQL case study questions require a unique approach. We’re here to teach you how to tackle them effectively.
Data analyst jobs at tech companies require a technical skillset. In this guide, we’ll break down the interview process and the most common data analyst interview questions.
Interview Query is partnering with Columbia University and Georgia Tech to help soon-to-be graduates prepare for technical data science interviews
Case study interviews for data engineers are one of the most challenging stages of the interview process.
Data analytics case study questions are notoriously difficult to study for and answer. Learn how to answer them from this guide.
These data analyst behavioral interview questions are open-ended and are designed to assess your experience, your ability to communicate, and whether you're the right fit.
See how one candidate transitioned from consulting to data science and landed a job at Facebook.
Considering an applied math major for data science? See how studying applied math can prepare you for data science jobs.
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