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About the Role

As a Senior or Staff Data Scientist focusing on Analytics, you'll serve as the statistical backbone of Bluefish’s Data Science team. You'll own experimentation and causal inference frameworks, produce rigorous methodological work, and function as the key escalation point for data-driven decision-making across the organization. You'll collaborate closely with Data Analysts, Applied Researchers, and cross-functional stakeholders to deliver insights, harden metrics, and deepen platform capabilities. This role offers a greenfield opportunity to define Bluefish's data science practice from the ground up, impacting both internal operations and customer-facing analytics products.

Responsibilities

Own experimentation end-to-end, including design, execution, and analysis of A/B tests and other experiments, and defining statistical significance frameworks.
Drive causal inference work by leading analyses that go beyond correlation to understand the mechanisms behind product and customer outcomes.
Serve as the analytics escalation point, acting as the go-to resource for deeper statistical rigor.
Build and maintain methodological standards by documenting and reviewing statistical methods, ensuring analytical quality and reproducibility.
Produce research, including authoring internal research papers, benchmark studies, and methodology documentation, and contributing to external-facing analyses.
Support ad-hoc deep-dives by responding to data requests from various departments with fast turnaround and clear narratives.

Requirements

Strong SQL and Python skills, including writing production-quality queries and analytical scripts.
Deep statistics background, including hypothesis testing, confidence intervals, power analysis, and causal inference.
Extensive experience designing and operating experimentation frameworks at scale.
Strong analytical and problem-solving abilities, with experience in data preprocessing, feature engineering, and model evaluation.
Business acumen to translate analytical findings into clear, actionable narratives for non-technical stakeholders.
Excellent communication and narrative crafting skills, with the ability to explain complex methods to diverse audiences.
Experience working with LLM or AI product data is a strong plus.
Familiarity with supervised learning techniques for predictive analytics use cases.
Exposure to unsupervised learning methods for customer segmentation or behavioral analysis.
Some experience working alongside or supporting ML model deployment, including understanding inference pipelines, feature stores, or model monitoring.
Comfort reading and interpreting NLP/ML research papers to stay current on methodological advances.
Experience with BI/visualization tools such as Looker, Omni, or Tableau.

Skills

SQL
Python
Statistics
Experimentation Frameworks
Causal Inference
Data Preprocessing
Feature Engineering
Model Evaluation
Business Acumen
Communication
Narrative Crafting
LLM/AI Product Data
Supervised Learning
Unsupervised Learning
ML Model Deployment
NLP/ML Research Interpretation
BI/Visualization Tools

Location

Berlin
Germany

Work Type

Hybrid
Remote

Experience Level

Senior
Staff

About the Company

Bluefish believes that AI represents the next major chapter of the internet, and that consumers will increasingly use AI to consume information and media online. Brands will need new tools and technologies to tell their stories to consumers online, and a new marketing ecosystem will be created around AI. Bluefish is building the platform that helps brands engage consumers on this new AI channel, with powerful enterprise tools to manage AI brand safety and engage consumers with thoughtful and personalized AI marketing experiences.
The Bluefish team is a tight-knit group of mar-tech industry veterans who previously helped build foundational ad-tech platforms now owned by Meta and Microsoft.
Bluefish is the leading AI marketing platform for the Fortune 500, recently announced a $43 million Series B growth financing co-led by Threshold Ventures and NEA with participation from multiple enterprise investors including Amex Ventures, TIAA Ventures, Salesforce Ventures, and Bloomberg Beta.
We are a globally distributed team, with business operations based in New York City and engineering based in Europe and New York.