Staff Data Scientist
- Compensation
- Not disclosed
- Location
- Berlin
- Work setup
- Onsite
- Seniority
- Staff
- Employment
- Not specified
- Experience
- Not specified
- Category
- Data science
- Posted
Skills
Must have
- 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.
Full description
This isn’t your regular job. Almedia is a place where those who want to push harder can accelerate their careers faster than anywhere else. We’re aiming to become Germany’s second bootstrapped unicorn. Almedia is already Europe’s #3 fastest-growing company in 2025 (FT1000).
We are building the future of marketing by rewarding our community of over 95 million users for engaging with our advertisers’ products. We are offering a new way to acquire users for the biggest companies in the world.
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.