Super Technologies - Staff Product Data Scientist
Upload My Resume
Drop here or click to browse · Tap to choose · PDF, DOCX, DOC, RTF, TXT
Requirements
• Technical Mastery • 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 and variance reduction techniques • Advanced statistical methods & causal inference • SQL proficiency for exploratory analysis and data validation (we use Snowflake). Enough to spec requirements for Analytics Engineers. Optimisation expertise is not required at this level. • SQL proficiency • Decision Science Mindset • A track record of producing decision memos, strategy recommendations, or business cases that measurably influenced product and commercial strategy. You care less about perfect models and more about driving measurable change. Your analyses are only successful if they move the needle. • track record of producing decision memos, strategy recommendations, or business cases • Executive Communication • You excel at transforming complex causal analyses into clear, compelling narratives. You can distil findings into “so what” recommendations for VP and C-suite audiences, making evidence accessible and actionable for strategic decision-making. • distil findings into “so what” recommendations for VP and C-suite audiences • Commercial & Product Acumen • You don’t just crunch numbers. You understand how data connects to business outcomes, product design, and customer behaviour. • Proactive Problem Framing • You don’t wait for perfectly-scoped requests. You reframe vague asks, propose alternative hypotheses, and drive analytical roadmaps based on business priorities. You’re comfortable with ambiguity and bias toward “what should we do?” over “what happened?”. • reframe vague asks, propose alternative hypotheses, and drive analytical roadmaps • Proven Track Record • Minimum 5+ years of relevant experience in analytics, data science, or product data science roles (ideally in product or commercial domains) where you’ve directly influenced strategy and growth through causal analysis and experimentation. • Minimum 5+ years • Education • Degree in Data Science, Statistics, Economics, Computer Science/Engineering, Mathematics, or a related quantitative field, or equivalent work experience. • We are a global technology company dedicated to building the future of entertainment and fan-centric experiences. • With commercial markets in Brazil, Belgium, Poland, Romania, Serbia, and Greece our company has evolved from a leading sports betting and gaming operator into a diversified product and tech organization, gathering more than 5,000 dedicated people across our teams. • Shaping the future of play • At Super, we are creating a unique entertainment ecosystem engaging millions of customers worldwide. Our product and technology teams in Amsterdam (the Netherlands), Madrid (Spain), Zagreb (Croatia), London (UK), and Bucharest (Romania) are building the playstack that will champion the future of play. • Our ambitious growth strategy focuses on expanding across Europe and Latin America while delivering immersive customer experiences and creating lasting value for our customers, partners, and communities. • Global recognition and standards • The company’s long-term strategy is supported by world-class investors. In 2019, Blackstone, the world’s largest alternative asset manager, made a strategic minority investment of €175 million. In 2025, we strengthened our financial position through a €1.3 billion refinancing agreement, reinforcing our partnership with Blackstone and enabling accelerated global expansion. • Super is committed to the highest standards of compliance, safety, and responsibility. As such, we are active members of the International Betting Integrity Association (IBIA) and the European Gaming & Betting Association (EGBA).
Responsibilities
• Be the Decision Engine • Run deep-dive analyses into customer behaviour, product usage, and commercial performance. • Go beyond surface-level metrics to uncover causal drivers behind phenomena using rigorous statistical methods. • Distinguish correlation from cause-and-effect. • Shape Strategy with Data • 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 that change the course of decisions, with quantified impact ranges and clear “so what” guidance for VP and C-suite stakeholders. • Deliver decision memos that change the course of decisions • Define Metrics & Specifications • Design KPI trees and define metric intent. • Specify requirements for Analytics Engineers to implement certified, production-grade data products. • Define tracking plans for instrumentation. • Specify dashboard requirements and acceptance criteria. • Ensure data capture supports decision-making needs. • Partner Across the Business • 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 to high-stakes discussions at the Director and VP levels. • Tackle Ambiguity • Super moves fast. The questions won’t always be clear. You’ll bring structure to chaos by translating broad business challenges into sharp analytical problems with measurable outcomes.
Benefits
• produce decision memos that influence what we should do about it • You’ll work in close partnership with Analytics Engineers, who build and maintain production data products. Your role is to define what needs to be measured and why, while AE ensures scalable, trustworthy data infrastructure. • define what needs to be measured and why
No credit card. Takes 10 seconds.