Cohere Health is transforming the healthcare landscape by addressing inefficiencies and focusing on patient care. Founded in August 2019, the company’s mission is to remove unnecessary barriers between patients and their doctors, ensuring treatments are swiftly approved and healthcare providers can focus on treatment rather than administrative issues.

As a Data Analyst at Cohere Health, you'll collaborate with a diverse team including clinicians, data scientists, and other experts to support and evaluate data-driven clinical programs. This role offers a dynamic and fast-paced environment with a focus on improving healthcare quality, patient outcomes, and cost efficiency. Adaptability, strong analytical skills, and effective communication are key for this position.

If you’re eager to join a rapidly growing digital health company, this guide by Interview Query will provide insights into the interview process, typical questions, and tips to help you succeed. 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 Cohere Health as a Data Analyst. Whether you were contacted by a Cohere 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 Cohere 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 Cohere 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 Cohere 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 Cohere 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 Cohere 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 Cohere Health.

Quick Tips For Cohere Health Data Analyst Interviews

Here are a few tips for acing your Cohere Health interview:

• Understand Cohere Health's Mission: Cohere Health focuses on improving patient healthcare experiences by removing friction from administrative processes. Familiarize yourself with their products and services to effectively answer situational and behavioral questions.
• Be Data-Driven: Cohere Health's data analyst role requires strong analytical skills and the ability to draw business and clinical insights. Brush up on your knowledge of data visualization tools like Tableau, programming languages like SQL or Python, and econometric models.
• Show Adaptability and Curiosity: The work is fast-paced and project-based, so demonstrate your ability to adapt to evolving needs and your curiosity to drive improvements in quality of care and patient outcomes.

Typically, interviews at Cohere Health vary by role and team, but commonly Data Analyst 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 find the maximum number in a list of integers. Given a list of integers, write a function that returns the maximum number in the list. If the list is empty, return None.

• Create a function convert_to_bst to convert a sorted list into a balanced binary tree. Given a sorted list, create a function convert_to_bst that converts the list into a balanced binary tree. The output binary tree should be balanced, meaning the height difference between the left and right subtree of all the nodes should be at most one.

• Write a function to simulate drawing balls from a jar. Write a function to simulate drawing balls from a jar. The colors of the balls are stored in a list named jar, with corresponding counts of the balls stored in the same index in a list called n_balls.

• Develop a function can_shift to determine if one string can be shifted to become another. Given two strings A and B, write a function can_shift to return whether or not A can be shifted some number of places to get B.

• What are the drawbacks of having student test scores organized in the given layouts? Assume you have data on student test scores in two different layouts. Identify the drawbacks of these layouts and suggest formatting changes to make the data more useful for analysis. Additionally, describe common problems seen in "messy" datasets.

• How would you locate a mouse in a 4x4 grid using the fewest scans? You have a 4x4 grid with a mouse trapped in one of the cells. You can scan subsets of cells to know if the mouse is within that subset. Describe a strategy to find the mouse using the fewest number of scans.

• 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.

• What factors could bias Jetco's study on boarding times? Jetco, a new airline, has the fastest average boarding times according to a study. Identify potential factors that could have biased this result and explain what you would investigate further.

• How would you design an A/B test to evaluate a pricing increase for a B2B SAAS company? You work at a B2B SAAS company interested in testing different subscription pricing levels. Describe how you would design a two-week-long A/B test to evaluate a pricing increase and determine if it is a good business decision.

• How much should we budget for the coupon initiative in total? A ride-sharing app has a probability (p) of dispensing a $5 coupon to a rider. The app services (N) riders. Calculate the total budget needed for the coupon initiative.

• What is the probability of both riders getting the coupon? A driver using the app picks up two passengers. Determine the probability that both riders will receive the coupon.

• What is the probability that only one of them will get the coupon? A driver using the app picks up two passengers. Determine the probability that only one of the riders will receive the coupon.

• What is a confidence interval for a statistic and why is it useful? Explain what a confidence interval is, why it is useful to know the confidence interval for a statistic, and how to calculate it.

• What is the probability that item X would be found on Amazon's website? Amazon has a warehouse system where items are located at different distribution centers. In one city, the probability that item X is available at warehouse A is 0.6 and at warehouse B is 0.8. Calculate the probability that item X would be found on Amazon's website.

• 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.

• What are time series models and why do we need them? Describe what time series models are and explain why they are necessary when we have less complicated regression models.

• How would you justify the complexity of building a neural network model and explain 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 the model and explain its predictions to non-technical stakeholders?

• 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? If you proceed, 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 random forest generates its forest of trees. Additionally, why would you choose random forest over other algorithms like logistic regression?

• How would you explain linear regression to a child, a first-year college student, and a seasoned mathematician? Explain the concept of linear regression to three different audiences: a child, a first-year college student, and a seasoned mathematician. Tailor your explanations to each audience's understanding level.

• What are the key differences between classification models and regression models? Describe the main differences between classification models and regression models.

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

Q: What does Cohere Health do?
Cohere Health illuminates healthcare for patients, their doctors, and others involved in a patient’s healthcare experience. They build software to reduce administrative hassles and ensure appropriate care plans are quickly approved, allowing everyone to focus on health rather than payment issues.

Q: What are the main responsibilities of a Data Analyst at Cohere Health?
As a Data Analyst, you will work closely with various teams to support data-driven clinical programs. Responsibilities include identifying target populations, defining success metrics, ongoing monitoring of programs, creating reports and visualizations, and proactively identifying opportunities for clinical speciality program improvement through data analysis.

Q: What skills and background are required for the Data Analyst position?
You should have a passion for improving the U.S. healthcare system, be a self-starter, possess strong communication skills, and have a minimum of 5 years' experience in the healthcare industry. Proficiency in SQL, R, Python, and tools like Tableau is essential. A Master's degree in a relevant quantitative discipline is also required.

Q: What is the company culture like at Cohere Health?
Cohere Health values empathy, kindness, and collaboration. They believe that diverse, inclusive teams create the most impactful work. The company fosters a supportive, growth-oriented environment and is deeply invested in the wellness and professional development of its employees.

Q: How can I prepare for the Data Analyst interview at Cohere Health?
To prepare for the interview, research the company thoroughly, understand their clinical content and programs, and practice common interview questions using Interview Query. Additionally, ensure your technical skills, especially in data analysis and visualization, are up-to-date.

If you want more insights about the company, check out our main Cohere Health 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 Cohere Health’s 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 Cohere Health data analyst 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!