Staff Data Scientist
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Our bar is high, and this is the best place for ambitious builders.
We’ve been bootstrapped and profitable from day one, and the FT1000 named us Germany’s fastest-growing company. We’re building the global leader in rewards, at a $1bn+ revenue run rate and climbing fast.
Staff Data Scientist
We're looking for a Staff Data Scientist with high ownership to work on meaningful challenges at scale.
You spot leverage points others miss: measurement systems that unlock pricing, experimentation infrastructure that multiplies output, causal models that rewrite unit economics. You own these end to end.
We value diverse technical lenses. Whether you are:
Causal inference specialist: propensity matching, DID, synthetic control, IV estimation. You turn observational chaos into rigorous insight.
Experimentation architect: designing multi-arm tests, MMM, MTA, uplift modelling. You define statistical rigor.
Systems thinker: building reward structures, pricing algorithms, ranking functions that balance engagement, conversion, and sustainable ROAS.
Zero to one builder: taking vague business questions into production data products.
What You'll Own
Measurement strategy. Design causal frameworks that reveal unit economics, attribution, and intervention impact. Own the gold standard documentation so others ship faster.
Experimentation infrastructure. Build platforms that enable rapid iteration and define statistical rigor without sacrificing speed.
High leverage models. Identify and own the models that move unit economics: pricing, ranking, user incentive systems. Partner with engineering to productionize rigorously.
Technical leadership. Mentor junior data scientists. Set the bar for how we think about causality, measurement, and trade offs. Drive clarity when stakeholders disagree.
Cross functional influence. Work alongside Product, Engineering, and Leadership to turn data insight into business action.
What We're Looking For
Proven autonomy. Track record moving unit economics through novel approaches. You own problems end to end.
Causal thinking. Deep experience with causal inference techniques (propensity matching, DID, synthetic control, IV estimation). You reason about causality, not just fit models.
Experimentation expertise. Led complex multi-arm experiments and designed or owned MMM, MTA, or uplift modelling systems. You understand type I and type II error costs.
Production maturity. Built and deployed models in product environments (Gaming, AdTech, user incentive systems preferred). You own metrics, monitoring, and decay.
Data engineering fluency. Comfortable with modern data stacks (dbt, Airflow, Kubernetes, Terraform). You architect alongside engineering, not just consume.
Communication and presence. Drive clarity in ambiguous situations. Translate complex analysis into decisions. Bring stakeholders along.
Why Almedia
Grow at Almedia: profitable from launch, higher revenue per employee than Big Tech.
Sharp, small team: we keep it small on purpose, every hire raises the bar.
Equity: every Berlin employee gets a stake.
Top of market baseline. Deliver outlier impact, earn accordingly.
We believe in fostering talent, evaluating all skill levels during the hiring process, and providing a clear path for growth. Almedia is an equal opportunity employer. We embrace and celebrate diversity, and encourage individuals from all backgrounds to apply.
Source: hiring system of Freecash, last checked 2026-11-06. You apply directly with the company.