Senior/Staff Data Scientist, Analytics
HybridBerlin, State of Berlin, Germany
Job Summary
Own experimentation end-to-end by designing, executing, and analyzing A/B tests while defining statistical significance frameworks. Drive causal inference work to understand mechanisms behind product and customer outcomes beyond correlation. Serve as the analytics escalation point for the organization, building and maintaining methodological standards across the team. Produce internal research papers, benchmark studies, and methodology documentation, plus support ad-hoc deep-dives for RevOps, MSS, Operations, and leadership. Collaborate with Data Analysts, Applied Researchers, and cross-functional stakeholders to deliver insights and harden reported metrics. This greenfield role defines Bluefish's data science practice from the ground up, directly impacting internal operations and analytics products for Fortune 500 brands on the new AI internet.
Required Qualifications
- Strong SQL and Python skills
- Deep statistics background
- Extensive experience designing and operating experimentation frameworks at scale
- Strong analytical and problem-solving abilities
- Experience in data preprocessing
- Experience in feature engineering
- Experience in model evaluation
- Business acumen
- Excellent communication and narrative crafting skills
- Ability to explain complex methods to product, sales, and executive audiences
- Experience working with LLM or AI product data
- Familiarity with supervised learning techniques
- Exposure to unsupervised learning methods
- Some experience working alongside or supporting ML model deployment
- Comfort reading and interpreting NLP/ML research papers
- Experience with BI/visualization tools
Desired Qualifications
- Experience working with LLM or AI product data is a strong plus
- Familiarity with supervised learning techniques (e.g., regression, classification, gradient boosting) for predictive analytics use cases
- Exposure to unsupervised learning methods (e.g., clustering, dimensionality reduction) for customer segmentation or behavioral analysis
- Some experience working alongside or supporting ML model deployment — understanding inference pipelines, feature stores, or model monitoring
- Comfort reading and interpreting NLP/ML research papers to stay current on methodological advances relevant to our data
- Experience with BI/visualization tools (e.g., Looker, Omni, Tableau)
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