One80 Intermediaries is a renowned specialty insurance brokerage and program manager that emphasizes innovative risk management solutions. As a Data Analyst at One80 Intermediaries, you will play a crucial role in analyzing data sets to derive actionable insights, enhance decision-making, and support strategic initiatives across the company. Candidates should be proficient in data analysis, statistical techniques, and possess strong problem-solving skills. This guide by Interview Query will help you prepare for your interview by detailing the process and offering tips and commonly asked questions to enhance your readiness and boost your chances of success. Let’s dive in!

Submitting Your Application

The first step is to submit a compelling application that reflects your technical skills and interest in joining One80 Intermediaries as a data analyst. Whether you were contacted by a One80 Intermediaries recruiter or have taken the initiative yourself, carefully review the job description and tailor your CV according to the prerequisites.

Tailoring your CV may include identifying specific keywords that the hiring manager might use to filter resumes and crafting a targeted cover letter. Furthermore, don’t forget to highlight relevant skills and mention your work experiences.

Recruiter/Hiring Manager Call Screening

If your CV happens to be among the shortlisted few, a recruiter from the One80 Intermediaries Talent Acquisition Team will make contact and verify key details like your experiences and skill level. Behavioral questions may also be a part of the screening process.

In some cases, the One80 Intermediaries data analyst hiring manager stays present during the screening round to answer your queries about the role and the company itself. They may also indulge in surface-level technical and behavioral discussions.

The whole recruiter call should take about 30 minutes.

Technical Virtual Interview

Successfully navigating the recruiter round will present you with an invitation for the technical screening round. Technical screening for the One80 Intermediaries data analyst role usually is conducted through virtual means, including video conference and screen sharing. Questions in this 1-hour long interview stage may revolve around One80 Intermediaries’ data systems, ETL pipelines, and SQL queries.

In the case of data analyst roles, take-home assignments regarding product metrics, analytics, and data visualization are incorporated. Apart from these, your proficiency against hypothesis testing, probability distributions, and machine learning fundamentals may also be assessed during the round.

Depending on the seniority of the position, case studies and similar real-scenario problems may also be assigned.

Onsite Interview Rounds

Followed by a second recruiter call outlining the next stage, you’ll be invited to attend the onsite interview loop. Multiple interview rounds, varying with the role, will be conducted during your day at the One80 Intermediaries office. Your technical prowess, including programming and ML modeling capabilities, will be evaluated against the finalized candidates throughout these interviews.

If you were assigned take-home exercises, a presentation round may also await you during the onsite interview for the data analyst role at One80 Intermediaries.

Quick Tips For One80 Intermediaries Data Analyst Interviews

• Should contain three tips for interviewing for this specific company based on interview experiences.

You should plan to brush up on any technical skills and try as many practice interview questions and mock interviews as possible. A few tips for acing your One80 Intermediaries interview include:

• Understand Their Business Model: One80 Intermediaries specializes in providing tailored insurance solutions. Study their products, services, and recent business activities to present informed answers that reflect your understanding.
• Be Data Driven: One80 Intermediaries’ data analyst interviews assess how well you can provide business-driving insights with data science. Brush up on your knowledge of statistics and probability, given these questions can be some of the hardest to solve.
• Highlight Communication Skills: A significant part of being a data analyst is not just analyzing data but also communicating insights effectively. Practice explaining complex data concepts in simple terms as this is crucial during the interviews.

Typically, interviews at One80 Intermediaries vary by role and team, but commonly Data Analyst interviews follow a fairly standardized process across these question topics.

• What are type I and type II errors in hypothesis testing? Explain the difference between type I (false positive) and type II (false negative) errors in hypothesis testing. Optionally, describe the probability of making each type of error mathematically.

• How would you select Dashers for Doordash deliveries in NYC and Charlotte? Doordash is launching delivery services in New York City and Charlotte. Describe the process for selecting Dashers (delivery drivers) and discuss whether the criteria for selection should be the same for both cities.

• How would you improve Google Maps and measure success? As a PM on Google Maps, suggest improvements for the app. Identify the metrics you would use to evaluate the success of these feature improvements.

• Why are job applications decreasing despite stable job postings? You observe that the number of job postings per day on a job board has remained constant, but the number of applicants has been decreasing. Analyze potential reasons for this trend.

• How would you analyze the performance of a new LinkedIn feature without A/B testing? As a data scientist at LinkedIn, you need to evaluate a new feature that allows candidates to message hiring managers directly during the interview process. Due to engineering constraints, A/B testing is not possible. Describe how you would analyze the feature's performance.

• Write a SQL query to select the 2nd highest salary in the engineering department. Write a SQL query to select the 2nd highest salary in the engineering department. If more than one person shares the highest salary, the query should select the next highest salary.

• Write a function get_ngrams to return a dictionary of n-grams and their frequency in a string. Write a function get_ngrams to take in a word (string) and return a dictionary of n-grams and their frequency in the given string.

• Write a function to determine if a string is a palindrome. Given a string, write a function to determine if it is a palindrome. A palindrome reads the same forwards and backwards.

• Write a query to find users currently "Excited" and never "Bored" with a campaign. Write a query to find all users that are currently "Excited" and have never been "Bored" with a campaign.

• Write a function moving_window to find the moving window average of a list. Given a list of numbers nums and an integer window_size, write a function moving_window to find the moving window average.

• What methods could you use to increase recall in product search results without changing the search algorithm? As a data scientist at Amazon, you want to improve the search results for product searches but cannot change the underlying logic in the search algorithm. What methods could you use to increase recall?

• What metrics would you use to track the accuracy and validity of a spam classifier model? You are tasked with building a spam classifier for emails and have built a V1 of the model. What metrics would you use to track the accuracy and validity of the model?

• How would you justify the complexity of a neural network model and explain its predictions to non-technical stakeholders? Your manager asks you to build a model with a neural network to solve a business problem. How would you justify the complexity of building such a model and explain the predictions to non-technical stakeholders?

• How would you evaluate and validate a decision tree model for predicting loan repayment? As a data scientist at a bank, you are tasked with building a decision tree model to predict if a borrower will pay back a personal loan. How would you evaluate whether using a decision tree algorithm is the correct model for the problem? How would you evaluate the performance of the model before deployment and after?

• When would you use a bagging algorithm versus a boosting algorithm? You are comparing two machine learning algorithms. In which case would you use a bagging algorithm versus a boosting algorithm? Provide an example of the tradeoffs between the two.

• What's the probability that the second card is not an Ace? You have to draw two cards from a shuffled deck, one at a time. Calculate the probability that the second card drawn is not an Ace.

• What are type I and type II errors in hypothesis testing? Explain the difference between type I errors (false positives) and type II errors (false negatives) in hypothesis testing. Bonus: Describe the probability of making each type of error mathematically.

• How much do you expect to pay for a sports game ticket? You can buy a scalped ticket for $50 with a 20% chance of not working. If it doesn't work, you'll need to buy a box office ticket for $70. Calculate the expected cost and the amount of money you should set aside for the game.

• Is the coin fair if it comes up tails 8 times out of 10 flips? You flip a coin 10 times, and it comes up tails 8 times and heads twice. Determine if the coin is fair based on this outcome.

• What is the difference between covariance and correlation? Explain the difference between covariance and correlation, and provide an example to illustrate the concepts.

What is the average salary for a Data Analyst at One80 Intermediaries?

Q: What is the interview process for a Data Analyst position at One80 Intermediaries? A: The interview process typically includes an initial phone screen with a recruiter, followed by a technical interview that may involve a data analysis task, and finally, an onsite or virtual interview where you discuss your approach and past experiences.

Q: What skills are required for a Data Analyst position at One80 Intermediaries? A: Strong analytical skills, proficiency in SQL, Python or R, data visualization tools like Tableau or Power BI, and experience with data warehousing. Soft skills like communication and problem-solving are also crucial.

Q: What is the company culture like at One80 Intermediaries? A: One80 Intermediaries fosters a collaborative and dynamic work environment. The company values innovation, continuous learning, and encourages employees to take initiative and bring new ideas to the table.

Q: What kind of projects will I work on as a Data Analyst at One80 Intermediaries? A: You will be working on projects involving data collection, cleaning, analysis, and reporting. The focus will be on using data to drive decision-making and improve business processes across various departments.

Q: How can I prepare for the Data Analyst interview at One80 Intermediaries? A: Familiarize yourself with the company’s business model and the industries they serve. Practice common data analysis problems and SQL queries using Interview Query to refine your technical skills. Be prepared to discuss past projects and how your skills can benefit the company.

Embarking on a career with One80 Intermediaries as a Data Analyst promises an enriching journey filled with opportunities to delve into impactful data insights and drive strategic business decisions. If you want more insights about the company, check out our main One80 Intermediaries Interview Guide, where we have covered many interview questions that could be asked. We’ve also created interview guides for other roles, such as software engineer and data analyst, where you can learn more about One80 Intermediaries' interview process for different positions.

At Interview Query, we empower you to unlock your interview prowess with a comprehensive toolkit, equipping you with the knowledge, confidence, and strategic guidance to conquer every One80 Intermediaries Data Analyst interview questions and challenges.

You can check out all our company interview guides for better preparation, and if you have any questions, don’t hesitate to reach out to us.

Good luck with your interview!