Strive Health is a rapidly growing healthcare company dedicated to transforming kidney care for patients suffering from chronic kidney disease (CKD) and end-stage renal disease (ESRD). With a unique data-driven approach, Strive Health is achieving better health outcomes and lower costs for patients and healthcare providers alike.

Stepping into Strive Health as a Data Engineer entails working with large and complex healthcare data sets, developing efficient data pipelines, and contributing to the scalability of their data architecture. As a Data Engineer, you'll be instrumental in optimizing data processing and analysis, which directly impacts patient outcomes and operational efficiencies.

In this guide, we’ll walk you through Strive Health's Data Engineer interview process, highlight some commonly asked questions, and provide valuable tips using Interview Query. 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 Engineer. 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 the Strive Health 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 Strive Health Data Engineer 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 Engineer 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 engineering roles, take-home assignments regarding data modeling, ETL processes, and system design may be incorporated. Apart from these, your proficiency against coding challenges, cloud computing services, and big data technologies 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 data pipeline 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 Engineer role at Strive Health.

Quick Tips For Strive Health Data Engineer Interviews

• Master the Fundamentals: Strive Health's data engineering interviews typically assess your prowess in SQL, ETL processes, and cloud-based services. Ensure you have a strong grip on these areas.
• Understand Healthcare Data: As a company focused on healthcare, understanding healthcare data workflows, regulations like HIPAA, and general industry challenges can give you a significant edge.
• Cultural Fit: Strive Health values team collaboration and a supportive work environment. Be prepared to answer behavioral questions that reflect the company's core values and demonstrate your ability to fit within their culture.

Typically, interviews at Strive Health vary by role and team, but commonly Data Engineer 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 if 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 tracking app? You work for a company with a sports app that tracks running, jogging, and cycling data. Formulate a method to identify users who might be cheating, such as driving a car while claiming to be on a bike ride. Specify the metrics and statistical methods you would analyze to detect athletic anomalies.

• 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 (with Newton's method) as the optimization method 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, and the PM finds 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, but due to engineering constraints, it can't be AB tested. How would you analyze the feature's performance?

• Customer success manager vs. free trial for Square's new product? The CEO of Square's small business division wants to hire a customer success manager for a new software product, while another executive suggests a free trial. What would be your recommendation for getting new or existing customers to use the new product?

• 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 Engineer at Strive Health?

Q: What is the interview process for the Data Engineer position at Strive Health?

A: The interview process at Strive Health for a Data Engineer position typically involves multiple stages, including an initial phone screen with a recruiter, a technical phone interview, and an onsite interview. The onsite interview consists of technical assessments, problem-solving exercises, and discussions to evaluate your skills and cultural fit.

Q: What are some common interview questions for a Data Engineer at Strive Health?

A: Common interview questions include technical questions on database management, data warehousing, ETL processes, and coding challenges. Be prepared to discuss your previous experience, specific projects you’ve worked on, and how you solved technical problems. Behavioral questions might also be asked to assess your fit within the team.

Q: What skills are required for a Data Engineer role at Strive Health?

A: Essential skills for a Data Engineer at Strive Health include proficiency in SQL, Python, and data warehousing solutions. Experience with cloud platforms (like AWS or Azure), ETL tools, and data modeling is also highly valuable. Strong problem-solving abilities and the capacity to work within a collaborative team environment are crucial.

Q: What is the company culture like at Strive Health?

A: Strive Health prides itself on fostering a supportive and innovative company culture. It values collaboration, continuous learning, and a commitment to improving healthcare through data. Employees are encouraged to be proactive, take ownership of their work, and contribute to the company’s mission of transforming kidney care.

Q: How can I prepare for an interview at Strive Health?

A: To prepare for an interview at Strive Health, you should research the company’s mission and values, practice technical interview questions, and refine your problem-solving skills. Utilize platforms like Interview Query to practice common Data Engineering questions and review your technical expertise. Be ready to discuss your previous projects and how they align with the role you’re applying for.

Embarking on your journey to become a Data Engineer at Strive Health is an exciting opportunity to shape the future of healthcare through innovative data solutions. To gain deeper insights into what the role entails, explore our detailed Strive Health Interview Guide where you'll find a plethora of interview questions and strategies that could be asked. We've also crafted specialized interview guides for roles like software engineer and data analyst, offering a comprehensive view of Strive Health's interview process across various positions.

At Interview Query, we equip you with the indispensable insights and preparation techniques required to master every challenge of your Strive Health Data Engineer interview. Delve into our vast array of company interview guides for an edge in your preparation. Should you have any questions, we're here to help you every step of the way.

Best of luck with your interview!