Truworth Wellness Health Data Analyst Interview: Rounds, Questions and Preparation

What the job involves

A Health Data Analyst in digital health supports wellness and population health programmes by cleaning, analysing, and reporting on data from apps, wearables, health risk assessments, and claims. Day to day, you build dashboards, track engagement and health outcomes, and share insights that help product, clinical, and client teams improve employee wellness offerings. In a fast-growing company, you often work with messy real-world data and need to explain findings clearly to non-technical stakeholders.

Role and Technical Knowledge

1. 1

   What is the difference between a health data analyst and a general data analyst in a digital health company?

   Highlight domain-specific data like step counts, HRA responses, biometric screening results, and claims, plus the need to understand health metrics and privacy rules.

2. 2

   How would you measure the success of a corporate wellness programme using data?

   Cover engagement metrics (app logins, challenge participation), health outcome metrics (BMI reduction, blood pressure control), and business metrics (client retention, claims cost trend).

3. 3

   Explain how you would handle missing values in a dataset of employee step counts.

   Discuss understanding why data is missing (device not worn, sync failure), options like deletion, imputation, or flagging, and how it affects analysis.

4. 4

   What are some common data quality issues in digital health data and how do you address them?

   Mention duplicate records, inconsistent units, outliers from faulty devices, time zone issues, and steps like validation rules, profiling, and documentation.

Practical Scenarios and Problem Solving

1. 5

   A client asks why their employees' average step count dropped last month. How would you investigate?

   Suggest checking data completeness, seasonality, app updates, device changes, and comparing with previous months and other clients before concluding a real decline.

2. 6

   You need to build a dashboard for a client showing health risk distribution across their workforce. What would you include?

   Include filters by department, age group, and risk category (low, moderate, high), plus clear definitions and privacy safeguards like minimum group size.

3. 7

   How would you analyse the impact of a 30-day step challenge on employee engagement and health?

   Compare pre, during, and post challenge metrics, use a control group if possible, and look at both participation and sustained behaviour change.

4. 8

   You find that 20 percent of users have unrealistic heart rate values. What do you do?

   Flag and exclude outliers with a documented rule, check device or integration errors, and communicate limitations to stakeholders rather than silently fixing.

Tools and Data Handling

1. 9

   Write a SQL query to find the number of active users per week for the last 8 weeks.

   Use date functions, group by week, and define active users clearly (for example, logged in or recorded an activity). Explain your assumptions.

2. 10

   How would you use Excel or Google Sheets to quickly summarise a survey of employee health risk assessments?

   Mention pivot tables, COUNTIFS, AVERAGEIFS, charts, and cleaning steps like removing duplicates and standardising text responses.

3. 11

   What steps would you take to ensure data privacy when sharing a report with a client?

   Cover de-identification, aggregation to avoid small cell sizes, access controls, and compliance with DPDP Act or HIPAA-like principles.

4. 12

   How do you decide between using Python and a BI tool for a given analysis?

   Discuss complexity, repeatability, audience, and speed. Python for cleaning and modelling, BI tools for interactive dashboards and stakeholder self-service.

Behavioural and HR Questions

1. 13

   Why do you want to work in digital health, and why this role?

   Connect personal interest in health, preventive care, or technology with the analyst role, and show awareness of challenges like data privacy and behaviour change.

2. 14

   Tell me about a time you worked with a messy dataset or a tight deadline.

   Use STAR format, focus on your actions, and highlight learning, communication, and delivering a usable result despite constraints.

3. 15

   How would you explain a complex data finding to a non-technical client or manager?

   Emphasise clear language, visual aids, focusing on the so-what, and avoiding jargon while still being accurate.

4. 16

   Where do you see yourself in two years in this field?

   Show interest in growing into deeper health analytics, population health, or data product roles, and mention skills you want to build.