Senior Data Scientist - Digital Pills

Digital Pills is a consulting company specialized exclusively in data, covering the full data value chain: data strategy, data engineering, analytics engineering, BI and data science.

The company works across two main areas, reducing customer acquisition costs and increasing customer lifetime value, for clients ranging from large international brands (including HelloFresh, Last Minute, Dolce & Gabbana, Arcaplanet) to non-profit organizations such as AIRC and Save the Children, to which the company donates 1% of its annual revenue.

Despite being a company of around 30 people, Digital Pills has recently started an international expansion with a hub in Berlin and is in the middle of a strategic transition: from bespoke consulting to a scalable model built on proprietary products and accelerators, developed starting from projects with its most strategic clients.

What you'll do

• Design, develop and validate solutions across classical machine learning, applied AI (agents, copilots, LLM-based services) and advanced statistics, bringing them to production with the right level of rigor
• Choose the right method for each context among experimentation, A/B testing, backtesting and causal inference, proving the business impact of what you build
• Own 2-3 client projects end-to-end in parallel, including relationships with senior client stakeholders
• Identify recurring patterns across projects and abstract them into reusable frameworks and accelerators, in collaboration with the CTO
• Mentor junior data scientists and contribute to the team's training roadmap
• Support Client Managers in pre-sales scoping, translating business requirements into technical architectures and realistic estimates
• Bring solutions to production in close collaboration with Data Engineering and Analytics Engineering colleagues
• Translate technical work into clear narratives for non-technical stakeholders

Technical requirements

• Strong Python (pandas, NumPy), ML/DL frameworks (scikit-learn, PyTorch, TensorFlow), and gradient boosting libraries (XGBoost, LightGBM, Catboost).
• Solid foundations in statistics, probability and ML theory
• Proven experience with model validation and evaluation, with the ability to avoid common pitfalls (overfitting, data leakage)
• Experience with A/B testing, backtesting and causal inference techniques
• At least one shipped LLM use case (RAG, agent, copilot or similar), with a pragmatic, anti-hype approach to AI adoption
• Advanced SQL, familiarity with data warehouses (BigQuery, Snowflake or similar)
• Hands-on experience with at least one cloud provider (GCP, Azure or AWS)
• Experience with model deployment, monitoring and logging in production
• Git and collaborative development, clean, testable and maintainable code beyond notebooks

Nice to have

• Analytics engineering experience with data from digital advertising and marketing platforms
• Experience turning one-off solutions into reusable internal tools, frameworks or products

You're the right person if you bring at least 8 years of experience in data science, machine learning or applied analytics, including at least 2 years in a senior capacity with technical ownership of projects and mentorship of junior colleagues, and you have a track record of models shipped to production with measurable business impact.

You're efficient, you don't let important details slip through the cracks, you speak plainly and honestly even about your models' limitations, you learn fast and absorb new information quickly.

You handle senior client relationships with confidence without being intimidated, you make important decisions independently and know when to raise your hand, and you're genuinely invested in growing the people around you.

Experience in consulting or in product companies with a strong data science practice, and experience working with international stakeholders, are a plus.

What the company offers

• RAL €55,000-65,000 (based on experience), CCNL Metalmeccanico Industria, paid over 13 months
• Annual bonus €4,0...