Data Scientist, Product

US Mobile•New York, NY

2d•$120,000 - $190,000•Hybrid

About The Position

We are looking for a Product Data Scientist who can turn data into clear, actionable insights that drive product and business growth. In this role, youâll partner closely with Product, Engineering, Marketing, and Operations teams to define success metrics, monitor performance, design experiments, and deliver reporting that guides decision-making. If you enjoy using data to tell stories, influence strategy, and uncover opportunities, this role is for you.

Requirements

5+ years of experience in product analytics, data science, or a related analytical role with a proven track record of delivering business impact.
Expert-level SQL skills for data extraction, transformation, and analysis.
Proficiency with BI and visualization tools (e.g., Tableau, Looker, Hex, or similar) to build clear, impactful dashboards and reports.
Familiarity with modern data modeling frameworks (e.g., dbt) and best practices in scalable analytics.
Demonstrated ability to perform exploratory analyses on complex datasets, tackling ambiguous, open-ended questions and translating findings into clear, actionable insights.
Excellent stakeholder management and communication skills, with the ability to distill complex findings into clear, compelling narratives for non-technical audiences.
Self-starter who is proactive, adaptable, and thrives in fast-paced, dynamic environments with evolving priorities.

Responsibilities

Partner with product and business teams to inform, influence, and execute product strategy and key investment decisions.
Analyze large, complex datasetsâconducting both ongoing and ad-hoc deep divesâto uncover patterns, trends, and opportunities that drive strategy.
Build and maintain dashboards and reports that deliver clear visibility into product usage, funnels, customer behavior, retention, and overall business performance.
Design and analyze A/B tests and product experiments to evaluate the impact of new features and product changes.
Design and build data models and pipelines that ensure reliable, scalable foundations for reporting and dashboards.
Translate complex data into actionable insights and communicate findings effectively to both technical and non-technical audiences.
Identify growth opportunities across acquisition, retention, monetization, and customer journey optimization.