Strive Health is dedicated to revolutionizing kidney care through early identification, engagement, and comprehensive coordinated care. By leveraging comparative and predictive data analytics, Strive Health's innovative model efficiently reduces emergency dialysis instances and inpatient utilization, significantly improving patient outcomes and experiences.

As a Data Analyst at Strive Health, you will support key analytical initiatives across the organization. You'll collaborate closely with leadership and market stakeholders, utilizing your expertise to develop robust analytics and self-service dashboards that enhance data-driven decision-making. This role demands proficiency in SQL, Excel, PowerPoint, and data visualization tools, with the potential for career growth in a supportive, award-winning environment.

In this guide, Interview Query will walk you through the application process, common interview questions, and valuable preparation tips to help you succeed in securing this rewarding position. Let's get started!

Submitting Your Application

The first step is to submit a compelling application that reflects your technical skills and interest in joining Strive Health as a Data Analyst. Whether you were contacted by a Strive Health 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 Strive Health 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 Strive Health 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 Strive Health 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 Strive Health’s 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 Strive Health 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 Strive Health.

Quick Tips For Strive Health Data Analyst Interviews

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 Strive Health interview include:

• Understand Kidney Care: Strive Health is committed to transforming kidney care. Familiarize yourself with the kidney care system, common challenges, and how data analytics can improve patient outcomes.
• Leverage Analytical Tools: Proficiency in SQL, Excel, PowerPoint, and other data visualization tools is crucial. Be sure to demonstrate your ability to analyze complex healthcare data sets.
• Embody Strive Health’s Values: Strive Health places a high value on resilience, tenacity, and compassionate care. Reflect these values in your responses to behavioral questions.

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

• How would you interpret coefficients of logistic regression for categorical and boolean variables? Explain how to interpret the coefficients of logistic regression when dealing with categorical and boolean variables.

• How would you design a machine learning model to classify major health issues based on health features? You work as a machine learning engineer for a health insurance company. Design a model that classifies whether an individual will undergo major health issues based on a set of health features.

• What metrics and statistical methods would you use to identify dishonest users in a sports app? You work for a company with a sports app that tracks running, jogging, and cycling data. Formulate a method to identify dishonest users, such as those driving a car while claiming to be on a bike ride. Specify the metrics and statistical methods you would analyze.

• Develop a function str_map to determine if a one-to-one correspondence exists between characters of two strings at the same positions. Given two strings, string1, and string2, write a function str_map to determine if there exists a one-to-one correspondence (bijection) between the characters of string1 and string2.

• Build a logistic regression model from scratch using gradient descent without an intercept term. Create a logistic regression model from scratch using basic gradient descent and the log-likelihood as the loss function. Do not include an intercept term or a penalty term. You may use numpy and pandas but not scikit-learn. Return the parameters of the regression.

• Why are job applications decreasing despite stable job postings? You observe that the number of job postings per day has remained stable, but the number of applicants has been decreasing. What could be the reasons for this trend?

• What would you do if friend requests on Facebook are down 10%? A product manager at Facebook informs you that friend requests have decreased by 10%. How would you approach this issue?

• How would you assess the validity of a .04 p-value in an AB test? Your company is running an AB test to increase conversion rates on a landing page. The PM reports a p-value of .04. How would you evaluate the validity of this result?

• How would you analyze the performance of a new LinkedIn feature without an AB test? LinkedIn has launched a feature allowing candidates to message hiring managers directly during the interview process. Due to engineering constraints, an AB test wasn't possible. How would you analyze the feature's performance?

• Should Square hire a customer success manager or offer a free trial for a new product? Square's CEO wants to hire a customer success manager for a new software product, while another executive suggests offering a free trial instead. What would be your recommendation?

• How would you build a fraud detection model using a dataset of 600,000 credit card transactions? Imagine you work at a major credit card company and are given a dataset of 600,000 credit card transactions. Describe your approach to building a fraud detection model.

• How would you interpret coefficients of logistic regression for categorical and boolean variables? Explain how to interpret the coefficients of logistic regression when dealing with categorical and boolean variables.

• How would you tackle multicollinearity in multiple linear regression? Describe the methods you would use to address multicollinearity in a multiple linear regression model.

• How would you design a facial recognition system for employee clock-in and secure access? You work as an ML engineer for a large company that wants to implement a facial recognition system for employee clock-in, clock-out, and access to secure systems, including temporary contract consultants. How would you design this system?

• How would you handle data preparation for building a machine learning model using imbalanced data? Explain the steps you would take to prepare data for building a machine learning model when dealing with imbalanced data.

What is the average salary for a Data Analyst at Strive Health?

Q: What is the main purpose of Strive Health? Strive Health aims to transform the kidney care system by leveraging early identification, engagement, and comprehensive coordinated care. We utilize comparative and predictive data analytics to enhance patient outcomes and experience from chronic kidney disease to end-stage kidney disease.

Q: Why should I consider applying to Strive Health? Strive Health has received multiple awards for being an excellent workplace, such as Forbes America's Best Startup Employers and Built In Colorado's Best Places to Work. Our diverse and inclusive environment, comprehensive wellbeing offerings, and various opportunities for professional development make us a great place to work.

Q: What are the responsibilities of a Data Analyst at Strive Health? The Data Analyst will support and advance enterprise-wide analytics and operational performance. Responsibilities include researching and developing analytical approaches, designing models and dashboards, performing ad-hoc analyses, and collaborating with internal and external teams to add value to partners.

Q: What qualifications are needed for the Data Analyst role? Candidates should have a Bachelor's degree with strong academic performance and at least one year of data analytics experience, preferably in healthcare. Proficiency in tools like Microsoft SQL, Excel, and PowerPoint is essential, with experience in AWS being a plus.

Q: How do I prepare for an interview at Strive Health? To prepare for an interview at Strive Health, thoroughly research the company and its mission. Practice common interview questions related to data analytics and healthcare. Interview Query is an excellent resource for practicing relevant questions and enhancing your technical skills.

Strive Health offers a unique opportunity to be part of a transformative journey in kidney healthcare. With our commitment to excellence and innovation, we've created a workspace recognized among America's Best Startup Employers in 2023 by Forbes. As a Data Analyst, you will join a passionate team dedicated to using data-driven insights to advance clinical and operational performance. To prepare effectively and gain deeper insights into the interview process, visit our Strive Health Interview Guide. At Interview Query, we're committed to equipping you with the tools and knowledge to succeed. Dive into our extensive resources and set yourself up for success. Good luck with your interview!