Staff Data Scientist
At a glance
Senior Data Science role at Almedia. Berlin · full-time · €100,000–€160,000 base.
dataroles summary, based on the employer's posting.
What you'll do
- Build causal measurement approaches to explain unit economics, attribution and the effects of interventions
- Create experimentation platforms that support fast testing while maintaining statistical standards
- Select and develop pricing, ranking or incentive models, then work with engineering to deploy them
- Coach junior data scientists and set technical standards for causal analysis and measurement
- Work with product, engineering and leadership to turn analytical findings into business decisions
What you bring
- You have led work that improved unit economics through original approaches and can take problems from start to finish
- You bring deep causal inference experience, including methods such as propensity matching or instrumental variables
- You have led complex multi-arm tests and built or owned MMM, MTA or uplift modeling systems
- You have deployed product models and managed their metrics, monitoring and performance decay
- You can work across modern data tools such as dbt, Airflow or Kubernetes, partnering with engineering on system design
Who this fits
This senior role suits a hands-on data scientist who can lead technical work, mentor junior colleagues and guide decisions when stakeholders disagree. The position is based onsite in Berlin.
From the employer
Our bar is high, and this is the best place for ambitious builders.
Bootstrapped and profitable from day one, Almedia is Germany’s fastest-growing company (FT1000). Join us as we build 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.
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