Product Data Scientist

  • Seattle, WA
  • Posted 7 hours ago | Updated 7 hours ago

Overview

On Site
Depends on Experience
Accepts corp to corp applications
Contract - W2
Contract - 5 Month(s)
No Travel Required

Skills

SQL
Product Analytics
A/B Testing & Experimentation
Statistics
KPI & Metrics Definition
Product Telemetry/Instrumentation
Data Visualization (Tableau/Power BI/Looker)
Snowflake
Python or R
Dashboard Automation
Data Pipelines (ETL/ELT)
Machine Learning Modeling
Cohort Analysis
User Segmentation
Agile/Scrum
Stakeholder Management
Data Storytelling & Executive Communication
Cross-functional Collaboration

Job Details

Role Overview

The Product Data Science team is seeking an experienced Data Scientist to support the development of data products and analytics capabilities that enable data-driven product development and decision-making. This role partners closely with Product, Engineering, User Experience, and leadership teams to deliver actionable insights that improve customer experience, engagement, and product adoption.

You will be embedded within specific product areas, building strong stakeholder relationships, defining product success metrics, designing experiments, and developing analytical and machine learning models. The ideal candidate is passionate about data-driven product development and fostering a culture of experimentation and continuous learning.


Key Responsibilities

  • Collaborate with cross-functional teams to analyze data and identify opportunities for product improvements, new features, and enhanced customer experience, engagement, and retention

  • Serve as the subject matter expert for product data strategy within supported product areas

  • Partner with Product Managers, Engineers, User Researchers, and leadership to prioritize insights, analyses, and data product opportunities that drive business impact

  • Define and implement product telemetry, establish key performance indicators (KPIs) with goals, and own recurring reporting on product usage and success

  • Partner with global analytics and data teams to automate data pipelines into Snowflake from multiple source systems

  • Design and build automated dashboards using internal and external data sources to enable self-service analytics for business users

  • Partner with product teams to design, execute, and analyze A/B tests, multivariate experiments, and machine learning models

  • Develop actionable insights and clearly present findings and recommendations to senior leadership

  • Evangelize analytical frameworks, models, and insights across business and technical stakeholders

  • Proactively identify and resolve roadblocks, working with cross-functional teams to drive progress with urgency and purpose


Basic Qualifications

  • Bachelor s degree in a quantitative field (Statistics, Mathematics, Computer Science, Economics, Finance, or similar) or equivalent professional experience

  • 7+ years of experience in data science, product analytics, or business analytics within a SaaS or cloud-based environment

  • Strong hands-on experience pulling data from multiple sources, joining disparate datasets, and translating large datasets into actionable insights

  • Advanced proficiency in SQL for data analysis and validation

  • Experience with data visualization tools such as Tableau, Power BI, or similar platforms, including dashboard design and data feed creation

  • Solid foundation in statistics and rigorous analytical techniques

  • Demonstrated experience solving real-world business problems using data

  • Strong ability to communicate technical and analytical findings to non-technical stakeholders

  • Experience working with product engineering teams to define and implement product telemetry

  • Familiarity with Agile/Scrum product development methodologies


Preferred Qualifications

  • Strong communication and leadership skills with the ability to influence across teams and organizational boundaries

  • Ability to present data visually and articulate insights clearly and concisely

  • Experience with A/B testing, cohort analysis, user segmentation, and core product analytics methodologies

  • Experience designing, building, and refining machine learning models

  • Proficiency in Python or R

  • Familiarity with data engineering processes and pipelines

  • Highly motivated, organized self-starter who thrives in a fast-paced, collaborative environment

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.