Senior Data Scientist (Marketing)

At Huuuge Games, we build top-grossing mobile games that bring people together through fun and social experiences - and our data is what powers it all.

As a Senior Data Scientist, you'll join an embedded team operating at the intersection of marketing and data science: sitting within the marketing function while collaborating closely with a group of highly skilled, curious, and driven data scientists who work with leading-edge tools, shape best practices, and transform data into real business impact. You'll be at the center of our data-driven marketing transformation — working on decisions that reach millions of players worldwide, from player behavior modeling to large-scale personalization systems.

This is a role with real autonomy, real stakes, and genuinely interesting problems. If you're excited by meaningful work, a team that pushes the craft forward, and the chance to build something that scales globally - this is where you want to be.

We are an in-office-first company and operate in a hybrid model (3 days from the office).

How will you make an impact with us? 

As a Senior Data Scientist embedded in the Marketing team at Huuuge, you'll play a key role in shaping how we acquire players, invest our marketing budget, and measure success. Your work will directly influence strategic decisions, budget allocation, and our understanding of what drives sustainable growth.

You'll be a trusted partner to Marketing stakeholders across UA, ASO, Creative, helping turn data into decisions and identifying opportunities before they become requests.

You will:

• Lead end-to-end Data Science initiatives, from problem definition and experimentation to implementation and business adoption, ensuring your work translates into measurable business outcomes.

• Build predictive models (LTV, ROAS, payback) that directly influence how marketing budgets are allocated across channels, geographies, and growth initiatives.

• Shape the future of our marketing measurement framework by advancing attribution methodologies through MMM, MTA, and incrementality testing, helping us better understand what truly drives performance.

• Proactively identify business opportunities, challenge assumptions, and bring forward data-driven recommendations that influence strategy and create measurable impact.

• Partner closely with Marketing teams, becoming a trusted advisor and the go-to expert for data-driven decision-making across the organization.

• Translate complex analyses into clear, actionable recommendations that stakeholders can quickly understand and confidently act upon.

• Develop scalable solutions and automate workflows to improve efficiency, accelerate decision-making, and enable teams to focus on higher-value work.

This is a high-ownership, high-visibility role where you'll have a direct impact on marketing strategy, budget allocation, measurement methodologies, and overall business performance.

This is the right job for you if you have:

• You bring 5+ years of hands-on Data Science or ML experience, ideally in product-oriented and highly data-driven environments.

• You love working at the intersection of data science and real business impact.

• Your foundations in statistics, ML, and experimental design are solid - you know why methods work and you can pick the right tool for the problem.

• You're fluent in Python (pandas, scikit-learn, TensorFlow/PyTorch, statsmodels) and SQL, and you're proficient with PySpark or big data environments when the scale demands it.

• You've worked with cloud infrastructure and ML tooling (Databricks, MLFlow, GitHub Actions) and care about building things that actually run reliably in production.

• You ask the right business question before reaching for a methodology, and you're willing to challenge your own assumptions when the data tells a different story.

• You genuinely enjoy translating complex analyses into clear, compelling narratives for non-technical audiences - and those conversations energize you rather than drain you.

• You thrive in fast-paced, ambiguous environments where priorities shift, ownership is expected, and no one needs to tell you what to work on next.

Surprise us with:

• Extensive practical experience in Product Data Science, with a strong focus on experimentation methodologies, causal inference and data-driven product decision-making.

• Experience building scalable, production-level data science solutions using best practices from software engineering.

• Experience with Bayesian modeling and probabilistic programming (PyMC, TFP, NumPyro).

• Passion for mobile games, understanding player behavior, and modeling game economy.

• Familiarity with mobile marketing ecosystems & concepts: attribution, UA channels, MMM.

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