Bull is a European innovation company developing powerful, sustainable, and sovereign digital solutions across high-performance computing, AI, and quantum technologies.
Main Mission
As a Senior Data Scientist at Bull, you will lead the technical direction on client engagements and turn ambiguous business problems into working AI products. You will set the approach, build the core solution, and bring the rest of the team along with you.
- Frame problems with clients, assess what is worth building, and determine when machine learning is not the right solution.
- Own solution design, select modelling approaches and architectures, and explain trade-offs to engineers and executives.
- Review code, mentor junior colleagues, and improve working practices across projects.
Project Responsibilities
- Profile and assess data during feasibility, including completeness, bias, label quality, and signal strength.
- Recommend whether to continue or stop a project, documenting the supporting evidence.
- Define success metrics that are accepted by institutions and remain meaningful at scale.
- Build evaluation harnesses and baselines and benchmark models against them.
- Conduct bias and fairness testing, particularly for systems affecting nationality, ethnicity, or vulnerable groups.
- Measure pilot results across sites and quantify implications for wider rollout.
- Contribute to fundamental rights impact assessments with the governance function.
- Support model iteration and error analysis.
Projects and Technology Stack
Projects span banking, insurance, manufacturing, pharmaceuticals, the public sector, and e-commerce, using call-centre logs, customer segmentation, IoT sensor streams, imagery, and web analytics.
Technologies include Python, SQL, Pandas, PySpark, Databricks, MLflow, PyTorch, Hugging Face, and LLM tooling. Solutions are deployed on Azure, AWS, Google Cloud Platform, and on-premises.
Teams are small, typically consisting of two to five people, and work in agile collaboration across engineering, analysis, data science, and product management.
Key Skills
Mandatory:
- At least 5 years of experience building data science or machine learning solutions that reached real users.
- Python, SQL, NoSQL, and standard data analysis tools.
- Hands-on depth in at least two of LLMs and generative AI, computer vision, or classical machine learning.
- Production model deployment experience, including containers, pipelines, monitoring, and retraining.
- Cloud experience with Azure, AWS, or GCP and distributed data processing with Spark, Databricks, or an equivalent.
- Strong applied statistics, including experiment design, uncertainty, calibration, and distinguishing real effects from hopeful results.
- Experience with RAG architectures, vector databases, embedding models, and modern AI tools.
- Familiarity with LLM frameworks such as LangChain or LlamaIndex.
- Experience evaluating machine learning systems against operational criteria.
- Ability to communicate negative results clearly and defend conclusions under pressure.
- Native Romanian and advanced English.
Nice to have:
- Experience in regulated industries such as pharmaceuticals, public sector, or banking.
- At least 2 years of team management experience.
- Databricks, OCR, graph neural networks, or fairness and bias auditing experience.
- Familiarity with EU AI Act high-risk evaluation and documentation requirements.
- Exposure to public administration, law enforcement, migration, or emergency services.
- Experience with spatio-temporal modelling, survival analysis, or anomaly detection on log data.
Why Join Us?
- Ownership of meaningful AI projects from initial client conversation through production.
- Collaboration with experienced engineers and scientists.
- Flexibility, remote work options, and continued connection between senior staff and hands-on technical work.
- Training and certification opportunities.
- Competitive salary and benefits package.
- Yearly reimbursement allowance and annual performance bonus.
- Career development opportunities and additional vacation days.