About Digital Pills
At Digital Pills, our mission is to empower businesses with the strategic use of data.
Our clients range from big corporations to elite B2C and B2B players. We also collaborate with foundations and non-profit organisations.
While growing quickly, we’re still a small company with a startup-like culture which offers maximum personal freedom and flexibility along with the ability to be agile.
Our Company Values are:
- Vertical Boutique: To compete with established players, vertical specialization is the essential ingredient. For us, this specialization is focused on data, which forms the core of our approach.
- Research and Development (R&D) and Training: We invest time in training and Research and Development projects. This keeps us constantly updated on the latest trends and technologies, ensuring cutting-edge service for our clients.
- People at the Center: We create a unique and motivating work environment to attract the best talents in the industry. Our corporate culture is geared toward maintaining high levels of quality in every aspect of our work.
- Social Impact on the Community: We are committed to making a positive contribution to the community. We donate 1% of our annual revenue to Pro-bono initiatives, and every member of our team dedicates 40 hours per year to non-profit projects. With our social commitment, we aim to make a difference in people’s lives and create a better world.
Joining our team means embracing these values and contributing to our mission of providing data-driven solutions that transform businesses.
Job description
This role is open to candidates ranging from Junior to Specialist profiles. As a Data Scientist, you will work on complex client projects end-to-end, from problem framing to production, with a level of autonomy proportional to your seniority.
The results we expect you to contribute are:
- Design, develop and validate solutions across classical machine learning, applied AI (agents, copilots, LLM-based services) and advanced statistics
- Choose the right method for the context: experimentation, A/B testing, backtesting and causal inference
- Bring solutions to production in close collaboration with Data Engineering and Analytics Engineering colleagues
- Translate technical work into clear narratives for non-technical stakeholders and senior client contacts
- Manage 2-3 client projects in parallel, with ownership scaling from contributor to end-to-end owner depending on seniority
Education & experience
- Master’s degree in a quantitative field (Computer Science, Statistics, Mathematics, Physics, Engineering, Data Science) or equivalent practical experience
- 1 to 5 years of experience in data science, machine learning or applied analytics roles
- Track record of models or analyses delivered in real-world contexts
Hard skills (essentials)
- Fluent in Italian, C1 English
- Data Science & Machine Learning
- Strong Python: pandas, numpy, scikit-learn
- At least one ML framework: PyTorch, TensorFlow, XGBoost or LightGBM
- Solid foundations in statistics, probability and ML theory
- Causal Inference & Experimentation: experience with A/B tests, backtesting and causal inference techniques.
- Data & Cloud Foundations
- Advanced SQL - Familiarity with data warehouses (BigQuery, Snowflake or similar)
- Hands-on experience with at least one cloud provider (GCP, Azure or AWS)
- Basic understanding of model deployment and monitoring
- Software Engineering
- Git and collaborative development
- Ability to write clean, testable and maintainable code beyond notebooks
Soft skills (essential)
- Efficiency. Able to produce significant output with minimal wasted effort.
- Attention to detail. Does not let important details slip through the cracks or derail a project.
- Honesty/integrity. Does not cut corners ethically. Earns trust and maintains confidence. Does what is right, not just what is politically expedient. Speaks plainly and truthfully.
- Intelligence. Learns quickly. Demonstrates ability to quickly and proficiently understand and absorb new information.
- Teamwork. Reaches out to peers and cooperates with supervisors to establish an overall collaborative working relationship.
- Enthusiasm. Exhibits passion and excitement over work. Has a can-do attitude.
Hard skills (desirable)
- Applied AI & LLM Integrations: experience with agents, copilot-like architectures and LLM-based applications, including prompt design and evaluation of generative outputs.
- Analytics Engineering: experience with data from digital advertising and marketing platforms.
What we offer
- Salary: RAL €32k - €42k (based on experience)
- €1500 - €2000 Annual welfare (based on experience)
- €2k - €4k annual bonus based on performance
- €8/day “buoni pasto”
- Continuous training and development: dedicated days for individual training, R&D & community of practice syncs
- Flexible workplace (8 days / month in-office presence is required)
Starting date: June 2026