B

Marketing Data Science Lead

brawl stars United Kingdom
Visa Sponsorship Relocation
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AI Summary

Lead the Marketing Data Science team in Helsinki or London, driving strategic measurement and AI integration across the full marketing mix. Own predictive modeling, causal inference, and technical standards while mentoring and growing data scientists. Requires 7+ years of applied data science in mobile gaming with hands-on ML and AI tooling experience.

Key Highlights
Lead cross-functional data science projects from business problem to shipped outcome
Own predictive modeling portfolio including pLTV, attribution, incrementality, and brand measurement
Shape Marketing Data Science roadmap with AI fluency and causal inference expertise
Mentor and grow a team of data scientists across multiple marketing domains
Key Responsibilities
Translate game team marketing questions into modeling and measurement work
Connect data science across performance/UA, brand, product marketing, influencer, and community domains
Own end-to-end predictive modeling and measurement portfolio (pLTV, attribution, incrementality, brand/lifecycle, signal and audience modeling)
Set technical standards for applied ML, causal inference, and mobile games data science
Integrate AI tools into creative media analysis, model diagnostics, automation, and decision processes
Shape Marketing Data Science strategy for 6-36 month horizon
Lead and mentor data scientists and analysts, set standards, and hire team members
Define measurement and forecasting models for new games before soft-launch
Technical Skills Required
Data Science Causal Inference Machine Learning PySpark MLOps
Benefits & Perks
Relocation assistance
Visa sponsorship
Nice to Have
7+ years applied Data Science with mobile gaming experience
Track record of leading data function including hiring
Hands-on with PySpark and modern MLOps
Marketing measurement under modern privacy constraints (SKAN/ATT)
MMM, brand lift, and quasi-experiments design at scale
Concrete examples of integrating AI/LLM tooling into workflows

Job Description


all positions

Helsinki/London – onsite – FullTime

Marketing Data Science Lead

We’re hiring a Lead to take our Marketing Data Science team forward. About half the role is project ownership and stakeholder leadership: turning questions and needs from game teams and marketing into well-scoped Data Science work, and shipping outcomes that change decisions. The other half is craft (senior data science expertise, mobile marketing measurement and AI fluency) while being the people lead for the team.

On top of that, we expect this Lead to shape where Marketing Data Science goes next. AI is changing what’s possible in measurement, automation, and decision support faster than our roadmap. We want someone with a point of view on that, who pushes us to act on it.

You’ll report to the Head of Marketing Data and Analytics and lead a team of data scientists and analysts across a variety of data science domains and marketing functions.

The Marketing Data Science team sits behind some of Supercell’s most consequential investment decisions. We measure, model, and forecast across the full mix of marketing investments and activities: performance/UA, brand, game teams marketing and live-ops, product marketing and lifecycle, influencer and partnerships, community and social.

What You'll Be Doing

  • Make game teams better at marketing decisions. Be close to game-team marketing analysts, live-ops/monetisation leads and marketers. Translate their questions into the right modeling and measurement work.
  • Connect data science across the full marketing mix. Performance/UA, brand, product marketing and lifecycle, influencer and community, events. Each has different measurement realities. Connect them into a coherent picture.
  • Own the predictive modeling and measurement portfolio. pLTV, attribution, incrementality, brand/lifecycle, signal and audience modeling - end to end, from methodology to production to adoption.
  • Set the technical bar. Strong, opinionated view of what good looks like in applied ML, causal inference, and mobile games business data science. Hands-on when the problem needs it. Decide what ships and what doesn’t.
  • Bring AI into how the team works. Use AI tools where they actually move the work - creative media analysis, model diagnostics, automation and decisions processes.
  • Shape where the function is going. You’re not just executing a roadmap - you have a view on what Marketing Data Science should be in 6-36 months, and you push us to get there.
  • Lead and grow the team. Support, mentor, coach on stakeholder communication, set standards, hire. Make the team better than it is today.

What it might look like in practice

Representative examples of what you might tackle in your first 6-12 months.

"Are our attribution and pLTV models shaping investments?"

  • Work with Games and marketing on how they actually use attribution and profitability evaluation - in what decisions, with what trust.
  • Close the gap between model and decision quality: what measurement is for, where it stops, what we use at the edges.

"Are game teams getting what they need from us?"

  • Map what game teams actually use and where they want more, reset the cadence and format of how we deliver insight and shape ways we support marketing decisions in games.
  • Pick one game and run a quarter as a deeper partnership. Prove what “good” looks like, then scale.

"How do we measure what attribution can’t see?", "How does brand, content, and community feed performance and back?"

  • Based on a portfolio of approaches )geo experiments, holdouts, synthetic controls, MMM, lift studies and more) build algorithms for decisions on how we invest in which channels.
  • Deliver answers on how brand, influencer, and community marketing initiatives move downstream player value and translate it into a clear narrative for marketing leadership and games.

"Where does AI actually move our work?"

  • Identify 2-3 places where AI materially changes what we can do - e.g. creative analysis at scale, model-drift diagnostics, decision-support for UA and game teams.
  • Pick one. Ship it. Measure whether it actually changes work.
  • Decide what team owns internally vs. lean on the wider Data and Insights organization.

"What does “good” look like for a new game on day one?"

  • Define measurement and forecasting models before soft-launch - across the mix, not just UA.
  • Productize the approach so it doesn’t get reinvented per game.

And many other things. We expect you to take ownership, work independently, and drive the topics you believe matter.

To excel here, you

  • Own projects and stakeholders, not just models. You take a business problem and solve it - from game team conversation to shipped outcome.
  • Have deep marketing measurement craft in mobile (or close to it). Built or owned measurement work in mobile gaming, apps or other digital business verticals. Comfortable across the mix - not only performance. Understand F2P games well enough to design best-in-class measurement around them.
  • Are a senior data scientist in practice, not just title. Strong applied stats, causal inference, classical ML, coding. Hands-on with infrastructure and models in production - CI/CD, monitoring, feature stores, large-scale data warehouses, realtime inference.
  • Use AI in your own work. You’ve actually integrated AI tooling into how you do data science. You have a view on where it changes the craft and where it’s noise.
  • Communicate clearly across audiences. Able to explain a model to a game lead in three minutes. Or a methodology to a senior DS in thirty. No 100-page decks. Comfortable saying "I don’t know" and "we shouldn’t do that because".
  • Lead and grow people. Mentored or managed data analysts/data scientists. Have views on standards, best practices, when to step in, when to step back.
  • Care about games and the players. You bring a player-centric lens even when the work is deep in LLM models business applications.
  • Operate well in autonomy and ambiguity. Don’t need a pre-set structure to be productive. Comfortable being wrong, learning fast, changing direction and impact over credit.

Would Be Nice if You Also Have

  • 7+ years applied Data Science / analytics with significant time in mobile gaming, apps, e-commerce or ad-tech
  • Track record of leading or significantly contributing to a data function, including hiring
  • Measurement experience across multiple types of marketing - not only performance/UA
  • Hands-on with PySpark and modern MLOps
  • Marketing measurement under modern privacy constraints (SKAN/ATT, deterministic-vs-probabilistic)
  • MMM, brand lift, and quasi-experiments design at scale
  • Concrete examples of integrating AI/LLM tooling into Data Science workflows

About The Team

You’ll lead the Marketing Data Science team within Marketing Data and Analytics, as a part of the Data and Insights organisation. The wider group also includes a Marketing Data team (automation, attribution and measurement infrastructure). Your team supports all our games - Brawl Stars, Clash of Clans, Clash Royale, Hay Day, new games - and all marketing functions across the organization.

You're based in Helsinki or London. You should expect to spend significant time in Helsinki HQ with key stakeholders.

–––

That's it about the role! Below, we've gathered some things we feel are important for you to know. Totally optional, but a highly recommended read.

Once you're ready to apply, just send us your application through the form on the bottom of the page.

–––

About Supercell

Supercell is a games company from Helsinki, Finland, with offices also in San Francisco, Seoul, Shanghai, and London. You might know us as the makers of Hay Day, Clash of Clans, Boom Beach, Clash Royale, and Brawl Stars. Our mission is to create great games that as many people as possible play for years and that are remembered forever.

So, how do we make great games? By putting together the best teams and giving them the freedom and independence to succeed. And by taking risks, failing, sharing learnings, and killing lots of projects.

Hey, You Might Love It Here!

Independent cells and trust are at the core of our culture. But it takes more than that to make great games. We take good care of our people, providing them with the compensation, work environment, and resources they need to succeed while having fun along the way.

You Are Not Your Job Title ™

Here, you won’t need to focus on chasing titles or climbing ladders. Internally, our job titles don’t include prefixes like Senior, Junior, Principal, or Director. Recognition isn’t tied to your title, as it doesn't define the impact you can have around here.

Benefits And Compensation

Luring you in with glitter, glamour, and gems isn't what we're about. We want you to enjoy your time here fully, so we structure our compensation and benefits with that in mind. It starts with perceiving you as a human being, not a resource.

Relocation? Yes!

No matter where you’re moving from, our dedicated mobility team and partners will support you throughout your move. We’ll ensure the process is as smooth as possible for you and anyone joining you – whether they’re family members of the human or animal kind!

Not Sure if You Should Apply?

Many candidates with great skills and experience second-guess themselves. The bar is high, but if this role excites you, apply! We’re here to help you succeed. Also, we're happy to learn about any specific accommodations you may need to fully engage in our recruitment process.

Wishing you all the best,

The Supercell Recruitment team

We’re hiring a Lead to take our Marketing Data Science team forward. About half the role is project ownership and stakeholder leadership: turning questions and needs from game teams and marketing into well-scoped Data Science work, and shipping outcomes that change decisions. The other half is craft (senior data science expertise, mobile marketing measurement and AI fluency) while being the people lead for the team.

On top of that, we expect this Lead to shape where Marketing Data Science goes next. AI is changing what’s possible in measurement, automation, and decision support faster than our roadmap. We want someone with a point of view on that, who pushes us to act on it.

You’ll report to the Head of Marketing Data and Analytics and lead a team of data scientists and analysts across a variety of data science domains and marketing functions.

The Marketing Data Science team sits behind some of Supercell’s most consequential investment decisions. We measure, model, and forecast across the full mix of marketing investments and activities: performance/UA, brand, game teams marketing and live-ops, product marketing and lifecycle, influencer and partnerships, community and social.

What You'll Be Doing

  • Make game teams better at marketing decisions. Be close to game-team marketing analysts, live-ops/monetisation leads and marketers. Translate their questions into the right modeling and measurement work.
  • Connect data science across the full marketing mix. Performance/UA, brand, product marketing and lifecycle, influencer and community, events. Each has different measurement realities. Connect them into a coherent picture.
  • Own the predictive modeling and measurement portfolio. pLTV, attribution, incrementality, brand/lifecycle, signal and audience modeling - end to end, from methodology to production to adoption.
  • Set the technical bar. Strong, opinionated view of what good looks like in applied ML, causal inference, and mobile games business data science. Hands-on when the problem needs it. Decide what ships and what doesn’t.
  • Bring AI into how the team works. Use AI tools where they actually move the work - creative media analysis, model diagnostics, automation and decisions processes.
  • Shape where the function is going. You’re not just executing a roadmap - you have a view on what Marketing Data Science should be in 6-36 months, and you push us to get there.
  • Lead and grow the team. Support, mentor, coach on stakeholder communication, set standards, hire. Make the team better than it is today.

What it might look like in practice

Representative examples of what you might tackle in your first 6-12 months.

"Are our attribution and pLTV models shaping investments?"

  • Work with Games and marketing on how they actually use attribution and profitability evaluation - in what decisions, with what trust.
  • Close the gap between model and decision quality: what measurement is for, where it stops, what we use at the edges.

"Are game teams getting what they need from us?"

  • Map what game teams actually use and where they want more, reset the cadence and format of how we deliver insight and shape ways we support marketing decisions in games.
  • Pick one game and run a quarter as a deeper partnership. Prove what “good” looks like, then scale.

"How do we measure what attribution can’t see?", "How does brand, content, and community feed performance and back?"

  • Based on a portfolio of approaches )geo experiments, holdouts, synthetic controls, MMM, lift studies and more) build algorithms for decisions on how we invest in which channels.
  • Deliver answers on how brand, influencer, and community marketing initiatives move downstream player value and translate it into a clear narrative for marketing leadership and games.

"Where does AI actually move our work?"

  • Identify 2-3 places where AI materially changes what we can do - e.g. creative analysis at scale, model-drift diagnostics, decision-support for UA and game teams.
  • Pick one. Ship it. Measure whether it actually changes work.
  • Decide what team owns internally vs. lean on the wider Data and Insights organization.

"What does “good” look like for a new game on day one?"

  • Define measurement and forecasting models before soft-launch - across the mix, not just UA.
  • Productize the approach so it doesn’t get reinvented per game.

And many other things. We expect you to take ownership, work independently, and drive the topics you believe matter.

To excel here, you

  • Own projects and stakeholders, not just models. You take a business problem and solve it - from game team conversation to shipped outcome.
  • Have deep marketing measurement craft in mobile (or close to it). Built or owned measurement work in mobile gaming, apps or other digital business verticals. Comfortable across the mix - not only performance. Understand F2P games well enough to design best-in-class measurement around them.
  • Are a senior data scientist in practice, not just title. Strong applied stats, causal inference, classical ML, coding. Hands-on with infrastructure and models in production - CI/CD, monitoring, feature stores, large-scale data warehouses, realtime inference.
  • Use AI in your own work. You’ve actually integrated AI tooling into how you do data science. You have a view on where it changes the craft and where it’s noise.
  • Communicate clearly across audiences. Able to explain a model to a game lead in three minutes. Or a methodology to a senior DS in thirty. No 100-page decks. Comfortable saying "I don’t know" and "we shouldn’t do that because".
  • Lead and grow people. Mentored or managed data analysts/data scientists. Have views on standards, best practices, when to step in, when to step back.
  • Care about games and the players. You bring a player-centric lens even when the work is deep in LLM models business applications.
  • Operate well in autonomy and ambiguity. Don’t need a pre-set structure to be productive. Comfortable being wrong, learning fast, changing direction and impact over credit.

Would Be Nice if You Also Have

  • 7+ years applied Data Science / analytics with significant time in mobile gaming, apps, e-commerce or ad-tech
  • Track record of leading or significantly contributing to a data function, including hiring
  • Measurement experience across multiple types of marketing - not only performance/UA
  • Hands-on with PySpark and modern MLOps
  • Marketing measurement under modern privacy constraints (SKAN/ATT, deterministic-vs-probabilistic)
  • MMM, brand lift, and quasi-experiments design at scale
  • Concrete examples of integrating AI/LLM tooling into Data Science workflows

Benefits And Compensation

Luring you in with glitter, glamour, and gems isn't what we're about. We want you to enjoy your time here fully, so we structure our compensation and benefits with that in mind. It starts with perceiving you as a human being, not a resource.

Relocation? Yes!

No matter where you’re moving from, our dedicated mobility team and partners will support you throughout your move. We’ll ensure the process is as smooth as possible for you and anyone joining you – whether they’re family members of the human or animal kind!

Not Sure if You Should Apply?

Many candidates with great skills and experience second-guess themselves. The bar is high, but if this role excites you, apply! We’re here to help you succeed. Also, we're happy to learn about any specific accommodations you may need to fully engage in our recruitment process.

Wishing you all the best,

The Supercell Recruitment team

This optional question helps us evaluate how we’re doing on diversity and inclusion. Answering or skipping this question will not affect your job application. The answers to this question are not collected nor seen on an individualized basis. Your answer will be used to assess our diversity and inclusion efforts only.

Consent request

You are about to consent to the retention of your data by Supercell. Supercell (we, that is) wants to process your data for the next 5 years. We ask for your consent as we want to act in compliance with data protection laws and regulations.

We collect your application data to manage and plan our recruitment activities globally. In the unhappy event that you don’t get selected, we will store your details for future opportunities. However, if you don’t wish to be contacted, please let us know.

The Supercell Applicant Database Privacy Policy is your friend in case you want to learn about topics such the processing of your personal data as well as when your personal data will be deleted if you don’t give your consent to retain it.

Note: The consent period lasts for 5 years

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