Super Technologies is hiring a Staff Product Data Scientist to operate at the intersection of product and strategy. You will own decision-making, problem framing, and hypothesis generation to shape product engagement for millions of customers, uncovering causal drivers and anticipating future trends.
What You'll Do
- Run deep-dive analyses into customer behaviour, product usage, and commercial performance.
- Go beyond surface-level metrics to uncover causal drivers using rigorous statistical methods.
- Distinguish correlation from cause-and-effect.
- Influence product roadmaps, commercial tactics, and marketing strategies by framing the right questions.
- Design and analyse experiments, including A/B tests and quasi-experiments.
- Deliver decision memos with quantified impact ranges and clear guidance for VP and C-suite stakeholders.
- Design KPI trees and define metric intent.
- Specify requirements for Analytics Engineers to implement certified, production-grade data products.
- Define tracking plans for instrumentation and specify dashboard requirements.
- Ensure data capture supports decision-making needs.
- Collaborate with Product Managers, Commercial leaders, Analytics Engineers, and Marketers.
- Lead problem-framing sessions, challenge assumptions, and reframe vague requests into testable hypotheses.
- Bring analytical rigour and structure to high-stakes discussions at the Director and VP levels.
- Translate broad business challenges into sharp analytical problems with measurable outcomes.
What We're Looking For
- Minimum 5+ years of relevant experience in analytics, data science, or product data science roles where you’ve directly influenced strategy and growth through causal analysis and experimentation.
- Advanced statistical methods & causal inference: A/B testing, confidence intervals, regression, quasi-experimental designs (difference-in-differences, synthetic controls, regression discontinuity), and an understanding of CUPED.
- SQL proficiency for exploratory analysis and data validation, enough to spec requirements for Analytics Engineers.
- Track record of producing decision memos, strategy recommendations, or business cases that measurably influenced product and commercial strategy.
- Excel at transforming complex causal analyses into clear, compelling narratives for VP and C-suite audiences.
- Understand how data connects to business outcomes, product design, and customer behaviour.
- Reframe vague asks, propose alternative hypotheses, and drive analytical roadmaps. Comfortable with ambiguity and bias toward 'what should we do?' over 'what happened?'.
- Degree in Data Science, Statistics, Economics, Computer Science/Engineering, Mathematics, or a related quantitative field, or equivalent work experience.
Technical Stack
- SQL
- Snowflake
Team & Environment
Work in close partnership with Analytics Engineers.
Super Technologies is committed to the highest standards of compliance, safety, and responsibility. We believe data is at the heart of every major decision and thrive in ambiguity, moving from messy questions to clear decisions that drive strategy.
