Product Data Analyst

Vienna, VA

Full Time

Mid Level

Product Data Analyst
Location: This is a HYBRID role. Employees are expected to collaborate in-person on a regular cadence (3 days a week). Candidates should be based within commuting distance of our Vienna, Virginia office. This is NOT a remote position.

Role Overview

The Product Data Analyst is responsible for analyzing complex datasets, conducting research to answer ambiguous, open-ended data questions, and delivering actionable insights to support product and business decisions. This role combines SQL analysis, basic Python-based data exploration, and dashboard and report development to transform raw data into meaningful information.

Key Responsibilities

Investigate and solve open-ended data questions by exploring datasets and identifying patterns, anomalies, or insights.
Write complex SQL queries to extract, analyze, and validate data from relational databases.
Develop basic Python scripts to automate analysis, data cleaning, and data processing tasks.
Conduct research to understand data sources, structures, and inconsistencies across systems.
Build and maintain dashboards and reports using Tableau or SQL-based reporting tools.
Translate analytical findings into clear summaries and visualizations for stakeholders.
Collaborate with product, engineering, and business teams to define metrics, validate data, and support data-driven decisions.

Core Skills

Strong SQL for data querying and analysis
Data visualization and dashboard development in Tableau
Analytical problem-solving and research skills
Basic Python for data manipulation and automation
Ability to work with ambiguous problems and incomplete data

Qualifications

Bachelor’s degree in Data Science, Statistics, Computer Science, Mathematics, or a related field
2–3 years of experience in a data analysis or business intelligence role
Proficiency in SQL with experience querying large relational databases
Experience with Tableau or a comparable data visualization platform
Familiarity with Python (pandas, NumPy, or similar libraries) for data processing
Strong analytical mindset with the ability to structure and solve ambiguous problems
Excellent written and verbal communication skills; ability to present findings to non-technical stakeholders
Experience in healthcare technology or a regulated industry is a plus

About careviso:

careviso is a cutting-edge, rapidly-growing healthcare technology company. By automating the impossible we’re able to solve the most complex problems in the healthcare industry in real-time: prior authorizations and financial transparency.

careviso created a complete technology platform that increases patient access to care by delivering cost estimates, administrative requirements, and approvals in real time. Our mission is to support patients, providers, and payors with total access to healthcare.

All employees must be authorized to work in the United States. careviso provides equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability or genetics. In addition to federal law requirements, careviso complies with applicable state and local laws governing non-discrimination in employment in every location in which the company has facilities.

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Have you personally written complex SQL queries (e.g., joins across 3+ tables, window functions, aggregations) in a production environment?*

Have you built Tableau dashboards from raw data (not just maintained or updated existing dashboards)?*

Have you used Python (pandas or similar) to clean, manipulate, or analyze datasets as part of your day-to-day work (not just coursework)?*

Have you independently validated data accuracy by identifying and resolving discrepancies across multiple data sources?*

Have you directly presented your own data analysis and insights to non-technical stakeholders or leadership?*

Are you comfortable completing a live SQL or data exercise during the interview process without the use of external assistance or AI tools?*

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