A Data Analyst at Headway plays a crucial role in scaling a high-growth marketplace that connects patients with accessible, affordable mental healthcare. At Headway, data is not merely a reporting tool; it is the infrastructure that drives therapist matching, optimizes clinical operations, and informs strategic product decisions. As a Data Analyst, you will sit at the intersection of product, engineering, and operations, translating complex marketplace dynamics into actionable business strategies.

Your work will directly impact how efficiently patients find the right care and how seamlessly providers can run their practices. Whether you are analyzing patient search behaviors, evaluating therapist onboarding funnels, or measuring the impact of new product features, your insights will guide the company's expansion. This role requires a blend of technical expertise, business acumen, and a deep alignment with the company's mission to rebuild the mental healthcare system.

The data environment at Headway is fast-paced and highly collaborative. You will handle large-scale datasets, build robust data models, and communicate your findings to cross-functional stakeholders. To succeed, you must be comfortable navigating ambiguity, structuring open-ended clinical and business problems, and championing data-driven decision-making across the organization.

The following questions are representative of the patterns and themes observed in real reported interview experiences for the Data Analyst position at Headway. While individual interview loops may vary based on team alignment, you should expect a heavy emphasis on SQL proficiency, structured problem-solving, and your ability to defend your past analytical work.

SQL & Technical Data Manipulation

• Write a SQL query using window functions to identify the most recent appointment booked by a patient and calculate the time elapsed since their previous booking.
• Given a table of therapist availability and patient searches, write a query to calculate the weekly conversion rate of searches to booked appointments.
• Explain the difference between a LEFT JOIN and an INNER JOIN in a dataset containing null values, and demonstrate how you would handle deduplication.

To succeed in the Headway interview loop, you must prepare to demonstrate both technical precision and strong communication skills. The hiring team looks for candidates who can not only write clean code but also translate that code into strategic business value.

Technical Rigor – You must demonstrate a strong command of relational databases and SQL. Practice writing clean, optimized queries under time pressure, focusing on window functions, complex joins, and aggregations.

Structured Problem-Solving – When presented with open-ended business cases, you need to apply a structured framework. Avoid diving straight into solutions; instead, clarify assumptions, define key metrics, and walk your interviewer through your analytical roadmap step-by-step.

Cross-Functional Communication – You will collaborate with product managers, engineers, and operations leaders. You must show that you can translate complex statistical and data concepts into clear, actionable recommendations for non-technical stakeholders.

Mission Alignment – Headway is deeply mission-driven. You should be prepared to articulate why you want to work in the mental health tech space and how your personal values align with the company's goal of making quality care accessible.

The interview process for a Data Analyst at Headway is designed to evaluate your technical capabilities, problem-solving structuredness, and cross-functional collaboration. The talent team is generally highly transparent about the stages, sharing information packets and direct links to the tools you will use during technical screens to help you prepare.

The process typically begins with a recruiter screen to discuss your background, compensation expectations, and your alignment with the company's mission. This is followed by a live SQL coding assessment to verify your technical baseline. Successful candidates then move to a comprehensive virtual onsite loop, which includes a case study presentation, a behavioral interview, and a cross-functional collaboration session.

The visual timeline above outlines the standard progression of the hiring loop. Candidates should use this timeline to pace their preparation, ensuring they allocate sufficient time to practice live coding before the technical screen and project defense strategies before the onsite. While the process is designed to move efficiently, scheduling availability can occasionally cause minor variations in the timeline.

Live SQL Coding & Technical Assessment

The live SQL assessment is a one-hour technical screen designed to evaluate your hands-on coding ability. You will work directly with a member of the data team to solve real-world data manipulation problems using a live coding environment.

Be ready to go over:

• Window Functions – Utilizing ROW_NUMBER(), RANK(), and LAG/LEAD to analyze sequential patient events.
• Complex Aggregations – Grouping and filtering data using HAVING clauses and conditional logic within SUM or COUNT statements.
• Data Cleansing – Handling null values, deduplicating records, and parsing strings or timestamps.
• Advanced concepts (less common) – Query performance optimization, understanding execution plans, and writing recursive Common Table Expressions (CTEs).

Example questions or scenarios:

• "Write a query to find the top three therapist specialties with the highest number of completed appointments in each state."
• "Calculate the rolling 7-day average of active therapists on our platform."

Data Analyst Case Study

The case study evaluates how you approach ambiguous business problems and structure your analytical thinking. You will be given a scenario based on Headway's marketplace operations and asked to identify key trends, define metrics, and recommend a course of action.

Be ready to go over:

• Metric Definition – Choosing the right primary and secondary metrics to measure product success or operational efficiency.
• Root Cause Analysis – Systematically breaking down a sudden drop in a key business metric.
• A/B Testing Frameworks – Designing experiments, determining sample sizes, and interpreting statistical significance.

Example questions or scenarios:

• "Our patient matching conversion rate dropped by 5% in a specific region. Walk me through how you would investigate this."
• "How would you design an analytical framework to measure the long-term retention of therapists onboarding onto our platform?"