Senior Data Scientist (Product Analytics & Experimentation)

Job Title: Senior Data Scientist (Product Analytics & Experimentation) Location: Remote PST Time Duration: 6months contract (high likelihood of extensions) We are seeking a Senior Product Data Scientist to support product innovation and data-driven decision-making for a high-impact, fast-paced consumer technology environment. This role focuses on 0→1 product development, experimentation, and translating complex data into strategic insights that shape product direction. You will partner closely with product managers, engineers, and cross-functional teams to define success metrics, design experiments, and influence product strategy through data. Ideal Candidate will have strong Product-focused Data Scientist with strong experimentation expertise, Demonstrated ability to turn data into product decisions and experience launching or supporting new product features or platforms Required Qualifications • 6+ years of experience in data science, product analytics, or related roles • Strong proficiency in SQL and Python for large-scale data analysis • Deep understanding of statistics, including: Hypothesis testing, Experimental design (A/B testing), Regression & inference methods • Proven ability to support new product development (0→1) using data insights • Experience working with cross-functional product teams to influence roadmap decisions • Strong communication skills with the ability to present complex findings in a clear, actionable way • Ability to manage multiple priorities in a fast-paced environment Preferred Qualifications • Experience with data pipelines or data engineering workflows • Background in consumer products, marketplaces, or advertising analytics • Familiarity with optimization or operational research techniques • Experience working in high-growth or large-scale product environments Responsibilities: • Analyze large, complex datasets to uncover trends, opportunities, and key drivers of business performance • Design and execute A/B tests and experimentation frameworks to evaluate new features and product changes • Define KPIs and measurement strategies for new and evolving products • Build scalable data analyses, dashboards, and reporting solutions for ongoing business insights • Develop statistical and analytical models to support forecasting, optimization, and decision-making • Translate ambiguous business problems into structured, data-driven approaches • Communicate findings clearly to both technical and non-technical stakeholders, influencing product decisions • Ensure data integrity, documentation, and methodological rigor across analyses