Resulticks is a cutting-edge, real-time marketing automation platform designed to help brands worldwide reach, acquire, and retain satisfied customers. With a foundation built by marketing, technology, and business management experts, Resulticks offers personalized engagement through AI-powered omnichannel orchestration, advanced analytics, and the world’s first marketing blockchain. Headquartered in Singapore and New York City, Resulticks has a significant global presence.

Resulticks is seeking an experienced Data Scientist to join their team. The ideal candidate will have strong mathematical and statistical skills, a creative mindset, and problem-solving abilities. Responsibilities include analyzing large data sets, developing insights, and presenting recommendations to senior management. Proficiency with analytical tools and effective teamwork across various disciplines are essential. If you are keen to make impactful business recommendations and thrive in a dynamic environment, this opportunity is for you. Prepare with Interview Query to ace your interview.

Submitting Your Application

The first step is to submit a compelling application that reflects your technical skills and interest in joining Resulticks as a Data Scientist. Whether you were contacted by a Resulticks 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, particularly in data analysis and statistics.

Recruiter/Hiring Manager Call Screening

If your CV happens to be among the shortlisted few, a recruiter from the Resulticks 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 Resulticks data scientist hiring manager will join 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 Resulticks Data Scientist role usually is conducted through virtual means, including video conference and screen sharing. Questions in this 1-hour long interview stage may revolve around data science methodologies, ETL pipelines, SQL queries, and Python/R programming.

You may also be asked to work on take-home assignments concerning product metrics, forecasting, optimization, and data visualization. Apart from these, your proficiency in 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 real-world scenario-based problems may also be assigned.

Onsite Interview Rounds

After 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 visit to the Resulticks 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 Scientist role at Resulticks.

Quick Tips For Resulticks Data Scientist Interviews

• Master the Tools: Ensure you are proficient with Tableau, SQL, Excel, and PowerPoint along with various programming languages and statistical software. Resulticks values hands-on experience with these tools.
• Case Study Preparation: Be ready to perform end-to-end analysis and present your findings clearly to stakeholders. Prepare for case studies that require a blend of technical and business recommendations.
• Culturally Fit: Resulticks takes pride in its collaborative and dynamic work environment. Be prepared to demonstrate your ability to work within multidisciplinary teams and handle multiple concurrent projects effectively.

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

• 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 to merge two sorted lists into one sorted list. Given two sorted lists, write a function to merge them into one sorted list. Bonus: Determine the time complexity.

• Create a function missing_number to find the missing number in an array. You have an array of integers, nums of length n spanning 0 to n with one missing. Write a function missing_number that returns the missing number in the array. Complexity of (O(n)) required.

• Develop a function precision_recall to calculate precision and recall metrics from a 2-D matrix. Given a 2-D matrix P of predicted values and actual values, write a function precision_recall to calculate precision and recall metrics. Return the ordered pair (precision, recall).

• Write a function to search for a target value in a rotated sorted array. Given a rotated sorted array and a target value, write a function to search for the target value. If the value is in the array, return its index; otherwise, return -1. Bonus: The algorithm's runtime complexity should be in the order of (O(\log n)).

• Would you think there was anything fishy about the results of an A/B test with 20 variants? Your manager ran an A/B test with 20 different variants and found one significant result. Would you suspect any issues with the results?

• How would you set up an A/B test to optimize button color and position for higher click-through rates? A team wants to A/B test changes in a sign-up funnel, such as changing a button from red to blue and/or moving it from the top to the bottom of the page. How would you design this test?

• What would you do if friend requests on Facebook are down 10%? A product manager at Facebook reports a 10% decrease in friend requests. What steps would you take to address this issue?

• Why would the number of job applicants decrease while job postings remain the same? You observe that the number of job postings per day has remained constant, but the number of applicants has been decreasing. What could be the reasons for this trend?

• What are the drawbacks of the given student test score datasets, and how would you reformat them for better analysis? You have data on student test scores in two different layouts. What are the drawbacks of these formats, and what changes would you make to improve their usability for analysis? Additionally, describe common issues in "messy" datasets.

• Is this a fair coin? 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.

• Write a function to calculate sample variance from a list of integers. Create a function that outputs the sample variance given a list of integers. Round the result to 2 decimal places. Example: Input: test_list = [6, 7, 3, 9, 10, 15] Output: get_variance(test_list) -> 13.89

• Is there anything suspicious about the A/B test results with 20 variants? Your manager ran an A/B test with 20 different variants and found one significant result. Evaluate if there is anything suspicious about these results.

• Write a function to return the median value of a list in O(1) time and space. Given a list of sorted integers where more than 50% of the list is the same repeating integer, write a function to return the median value in O(1) computational time and space. Example: Input: li = [1,2,2] Output: median(li) -> 2

• What are the drawbacks of the given student test score data layouts? You have data on student test scores in two different layouts. Identify the drawbacks of these layouts, suggest formatting changes for better analysis, and describe common problems in "messy" datasets.

• How would you evaluate the suitability and performance of a decision tree model for predicting loan repayment? You are tasked with building a decision tree model to predict if a borrower will repay a personal loan. How would you evaluate whether a decision tree is the correct model for this problem? If you proceed with the decision tree, how would you evaluate its performance before and after deployment?

• How does random forest generate the forest and why use it over logistic regression? Explain how a random forest generates its forest of decision trees. Additionally, discuss why you might choose random forest over other algorithms like logistic regression.

• When would you use a bagging algorithm versus a boosting algorithm? Compare two machine learning algorithms. In which scenarios would you use a bagging algorithm versus a boosting algorithm? Provide examples of the tradeoffs between the two.

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

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

What is the average salary for a Data Scientist at Resulticks?

Q: What is Resulticks?
Resulticks is a fully integrated, real-time marketing automation platform built to help brands worldwide reach, acquire, and retain satisfied customers. With advanced CDP technology and AI-powered omnichannel orchestration, Resulticks offers complete analytics and next-best engagement strategies for personalized customer interactions.

Q: What are the key responsibilities for the Data Scientist position at Resulticks?
You will work with large, complex data sets, applying advanced analytical methods. This includes conducting end-to-end analysis, developing a comprehensive understanding of data structures, and presenting business recommendations. Additionally, you will interact cross-functionally to research and develop forecasting and optimization methods.

Q: What qualifications and skills are required for this role?
The ideal candidate should have a minimum of 5 years of relevant work experience in data science, proficiency with tools like Tableau, SQL, Excel, PowerPoint, and programming languages. You should also possess strong mathematical and statistical analysis skills, and the ability to work in a dynamic, research-oriented group.

Q: What is the company culture like at Resulticks?
Resulticks values diversity and inclusion, prohibiting discrimination and harassment of any kind. The company fosters a collaborative and optimistic environment where you can confidently present your findings and work with multidisciplinary teams.

Q: How can I prepare for an interview at Resulticks?
To prepare for an interview at Resulticks, research the company's platform and offerings. Practice common interview questions, and review your technical skills relevant to data science. Interview Query is a great resource to practice and hone your interview skills.

If you want more insights about the company, check out our main Resulticks 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 Resulticks’ 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 Resulticks data scientist interview question and challenge.

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!