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SeniorУдалённоПолная занятость

Senior Commercial Data Scientist

Оценка ИИ

Высокая оценка обусловлена сильным брендом компании, поддержкой Blackstone и стратегической значимостью роли. Это позиция для тех, кто хочет реально влиять на бизнес, а не просто строить модели.


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Сложность вакансии

ЛегкоСложно
Оценка ИИ

Роль требует высокого уровня владения методами причинно-следственного вывода (causal inference) и опыта взаимодействия с топ-менеджментом. Кандидат должен уметь не просто анализировать данные, но и формировать бизнес-стратегию.

Анализ зарплаты

Медиана75 000 $
Рынок55 000 $ – 100 000 $
Оценка ИИ

Указанная роль Senior уровня в международной технологической компании в Бразилии предполагает зарплату выше среднего по рынку, особенно учитывая требования к Causal Inference. Наш прогноз базируется на данных для Senior Data Scientists в финтех и гейминг секторах региона.

Сопроводительное письмо

I am writing to express my strong interest in the Senior Commercial Data Scientist position at Superbet. With over five years of experience in product data science and a deep specialization in causal inference and experimental design, I am drawn to Superbet’s commitment to making data-driven decisions the heart of its global strategy. I have a proven track record of translating complex customer behavior data into actionable decision memos that directly influence product roadmaps and commercial outcomes.

In my previous roles, I have successfully utilized advanced statistical methods such as difference-in-differences and synthetic controls to move beyond simple correlations and uncover true causal drivers. I pride myself on my ability to bridge the gap between technical analysis and executive-level strategy, ensuring that every insight leads to a clear 'so what' for stakeholders. I am excited by the prospect of bringing this expertise to Superbet's fast-paced environment and helping shape the future of entertainment across your international markets.

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Откликнитесь в superbet уже сейчас

Присоединяйтесь к Superbet и станьте двигателем стратегических решений, используя силу причинно-следственного анализа!

Описание вакансии

It’s an exciting time to join us! We’re entering new markets, developing new technologies, and moving step by step towards our goal of exciting the world. As our business grows, the number of exciting people initiatives grows with it, and we’re looking for a new colleague to partner with our team to bring these to life.

The Role

At Super, data isn’t a support function. It’s at the heart of every major decision we make.

As a Senior Product Data Scientist, you’ll operate at the intersection of product and strategy, owning decision-making, problem framing, and hypothesis generation. Your work won’t sit in slide decks. It will directly shape how millions of customers engage with our products.

This is a role for a very special kind of data scientist: someone who loves hard problems, thrives in ambiguity, and gets energised by moving from messy questions to clear decisions that drive strategy.

You’ll be expected to not just report what happened, but to uncover why through causal inference, anticipate what’s next, and 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.

What You’ll Do

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 Directors.

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 level.

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.

What We’re Looking For

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
  • 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.

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.

Executive Communication

You excel at transforming complex causal analyses into clear, compelling narratives. You can distil findings into “so what” recommendations for Directors and other Commercial Stakeholders, making evidence accessible and actionable for strategic decision-making.

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?”.

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.

About us

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, and Serbia, 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).

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Навыки

  • A/B Testing
  • Python
  • SQL
  • Statistics
  • Data Visualization
  • Snowflake
  • R
  • Causal Inference
  • Regression
  • CUPED

Возможные вопросы на собеседовании

Вакансия делает упор на причинно-следственную связь. Важно понять, как кандидат выбирает методы для оценки влияния фичи.

Расскажите о случае, когда вам пришлось использовать квазиэкспериментальный дизайн (например, Diff-in-Diff). Почему вы выбрали именно этот метод?

В описании упоминается CUPED. Это показывает техническую глубину в области оптимизации A/B тестов.

Как бы вы объяснили стейкхолдерам преимущество использования CUPED для снижения дисперсии в экспериментах?

Роль предполагает работу с неопределенностью и влияние на решения директоров.

Опишите ситуацию, когда ваши аналитические выводы противоречили мнению руководства. Как вы аргументировали свою позицию?

Вакансия требует навыков постановки задач для Analytics Engineers.

Как вы подходите к проектированию KPI-дерева для нового продукта и какие требования вы предъявляете к качеству данных на входе?

Акцент на 'Decision Science'. Анализ ценен только если он меняет бизнес.

Приведите пример вашего 'decision memo', которое привело к измеримому изменению в продуктовой стратегии компании.

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