Product Data Analyst (Academic Background)
Role Overview
This mid-level Product Data Analyst role involves partnering with the Product team to inform feature development through data analysis, including designing experiments, analyzing user behavior patterns, and building dashboards in Mixpanel. Day-to-day tasks include writing SQL queries, developing Python scripts for data processing, maintaining the Snowflake data warehouse, and conducting qualitative user research. The hire will impact product improvements and health outcomes by providing actionable insights and supporting academic reporting in a remote, innovation-driven environment.
Perks & Benefits
This is a fully remote position with flexible hours aligned to 9-5pm PST, offering a competitive monthly salary of $3,500-4,500 depending on experience. The company fosters an inclusive culture focused on personal growth, continuous learning, and belonging, with opportunities for career advancement in a supportive, innovation-driven team. As a contractor, you'll have the chance to contribute to grant-funded projects and make a meaningful impact on health behavior change through data-driven insights.
Full Job Description
Job Title: Product Analyst (Academic Background)
Location: Remote (LATAM)
Working Hours: Monday to Friday, 9:00 AM – 5:00 PM PST
Compensation: $3,500 – $4,500 USD/month (based on experience)
About the Company
Our client is a neuroscience-based technology company focused on transforming health behavior change through a positive, iterative approach to habit formation. Their platform enables users to test evidence-based healthy habits in real time — eliminating guesswork and fostering a mindset of continuous improvement.
Our client operates as a 100% remote team, headquartered on a retreat in the Santa Cruz mountains, and is deeply committed to belonging, personal growth, and lifelong learning.
About the Role
We are hiring a Product Analyst to join the team as a contractor. This role sits at the intersection of product, data, and behavioral science. You will analyze user behavior, product performance, and experimental results to drive smarter product decisions and better health outcomes.
You’ll collaborate closely with Product, Engineering, and Research teams, contributing to both commercial product development and academic research initiatives.
Key Responsibilities
Product & Data Analytics
Partner with Product to inform feature development and behavioral interventions through data
Design hypotheses, run experiments, and analyze results
Conduct exploratory and statistical analyses to uncover user behavior patterns and performance trends
Build and maintain Mixpanel dashboards to track user engagement and product health
Define and validate Mixpanel event tracking and troubleshoot instrumentation issues
Data Engineering & Analytics
Write SQL to query internal databases and Snowflake
Develop Python scripts for data processing, automation, and statistical analysis
Build and maintain Fresh Tri’s Snowflake data warehouse, including schema design and data ingestion
Create and maintain BI visualizations for stakeholders
Partner with Engineering to ensure data quality and pipeline reliability
Research & Reporting
Conduct qualitative user research (e.g., interviews) to complement quantitative data
Support academic and business reporting with actionable insights
Write methods and results sections for research manuscripts
Perform advanced statistical testing for ad hoc analysis
Lead or support grant-funded projects and applications
Design and execute statistical analysis plans
Clean, merge, and prepare datasets for analysis
Conduct literature reviews and support commercial and client research
Requirements
2+ years in Product Analytics, Growth Analytics, Data Analytics, or a similar role supporting digital products
Strong experience with Mixpanel (dashboards, event tracking, taxonomy, validation)
Proficiency in SQL for structured and unstructured data
Experience using Python for analysis, automation, or data processing
Experience with Snowflake, including pipelines, data sources, and visualizations
Solid foundation in statistics, including experiment design, hypothesis testing, and regression
Ability to read and understand application code for debugging analytics instrumentation
Experience with Google Analytics, A/B testing tools, and experimentation frameworks is a plus
Bachelor’s degree in a technical, quantitative, or behavioral science field preferred
Strong communication skills — able to translate complex analysis into clear business insights
Curious, collaborative, and impact-driven
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