MUBI
Senior Product Data Scientist

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About MUBI
MUBI is a global streaming service, production company and film distributor dedicated to elevating great cinema. To make this possible, we create, curate, acquire and champion visionary films, bringing them to audiences all over the world. We have a team of brilliant, dedicated and passionate people to help bring our mission to life. From London to New York, Istanbul to Paris, and Berlin to Mexico - we work together to realize MUBI’s vision.
That’s where you come in! Join our global team and help us make great cinema accessible to everyone, everywhere.
About The Role
We're looking for a Senior Product Data Scientist to help us understand what drives engagement and retention of our subscribers, and to raise the bar for how we use data and experimentation to make product decisions.
This role sits at the intersection of product analytics and data science. You'll spend part of your time embedded in our Engagement & Discovery squad, working day to day with product managers, engineers and designers as the data voice in a multidisciplinary team. The rest of your time you'll work within the Data Science team on deeper analyses and models that shape how MUBI acquires, engages and retains film lovers.
Experimentation at MUBI is growing, and you'll play a central part in maturing it: bringing rigour to how we design tests, define success, and turn results into decisions. You won't wait to be handed questions - the best person for this role is independently curious about how MUBI's business works and comes to the team with ideas of their own.
Where you'll have impact
- Champion a culture of experimentation. Help establish the frameworks, metrics and habits that make experimentation the default way we make product decisions: design A/B tests, define success and guardrail metrics, analyse results, and own the "should we ship this?" recommendation.
- Embed with a product delivery team. Spend part of your week inside our Engagement & Discovery squad, shaping the roadmap with data - sizing opportunities, defining metrics for new features, and making sure we learn from everything we ship.
- Bring data science into the room. Propose the analyses, models and experiments the team didn't know to ask for, and communicate them in a way that lands with product managers, engineers and non-technical stakeholders.
- Understand what drives the business. Dig independently into what drives engagement and retention of MUBI's subscribers - across viewing behaviour, curation, pricing and lifecycle - and turn what you find into action.
- Build models that inform decisions. Develop churn and propensity models, LTV estimates and behavioural segmentations that sharpen how we target, retain and delight subscribers.
- Put AI to work. Use tools like Claude Code to accelerate analysis and modelling, and help the team do the same.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
What you'll bring
- 3-5 years of experience in product analytics, product data science, or a similar role, ideally in a consumer subscription or digital product business.
- A strong grounding in data science methods - statistics, experimentation and machine learning - ideally with a postgraduate qualification in data science, statistics or a related quantitative field.
- Strong SQL and Python. This is core to the role - you'll use both daily for analysis and modelling.
- Hands-on experience designing, running and analysing experiments, and the statistical grounding to know when an A/B test is the wrong tool.
- Familiarity with Claude Code or similar AI tools, and an appetite for working out how they make you faster and better.
- Strong communication and collaboration skills - you can turn an analysis into a clear recommendation for product managers, engineers and other stakeholders.
- An independent mindset and genuine curiosity about what drives a subscription business - you generate your own questions rather than waiting for a brief.
- Detail-oriented and pragmatic, with a "no task too small" attitude.


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Nice to have
- Experience with dbt for developing data products.
- Familiarity with Snowflake and modern BI tools (we use Omni).
- Experience in a fast-paced, high-growth environment (e.g. startup or scale-up).
- Genuine interest in film and in MUBI's mission.
Our Commitment
We want to make cinema accessible to everyone. We believe people from different backgrounds bring different ideas that foster innovation and engagement, allowing us to attract great people to develop the best experience for our users.
MUBI is committed to being an Equal Opportunity Employer. That means it's our responsibility to ensure that all candidates are not discriminated against in our hiring processes and our employment decisions based on their race, color, religion, nationality or ethnic origin, age, gender identity or expression, sex, marital status, physical or mental disability, socioeconomic background, sexual orientation, family or parental status, or any other applicable characteristic.
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