Associate Specialist, Data Science

Contribute to Generative AI and Agentic AI solutions, including LLM applications, RAG, AI assistants, AI agents, and agentic workflows.

Build high-quality and reusable analytical and AI components using Python, SQL, and modern AI/ML frameworks.

Apply appropriate evaluation approaches to assess model and AI solution performance, reliability, and business relevance.

Take ownership of assigned solutions and workstreams, with accountability for quality, timelines, documentation, and outcomes.

Collaborate with engineering and MLOps teams to support deployment, monitoring, maintenance, and continuous improvement of AI/ML solutions.

Contribute to a collaborative Data Science & AI community by sharing knowledge, reusable assets, best practices, and learnings across teams and markets.

Required Experience, Skills and Qualifications:

Bachelor or Master degree in computer science, Data Science, Statistics, Mathematics, Engineering, or another relevant quantitative discipline.

2+ years of relevant experience in Data Science, Machine Learning, Advanced Analytics, or AI.

Strong hands-on experience with Python and SQL.

Good understanding of machine learning, statistics, feature engineering, experimentation, model evaluation, and validation.

Hands-on experience with common ML libraries and frameworks such as scikit-learn, XGBoost, TensorFlow, PyTorch, or equivalent.

Ability to work with complex datasets and translate business questions into structured analytical approaches.

Strong analytical thinking and critical thinking skills.

Good communication and collaboration skills, with the ability to work effectively across technical and business teams.

Demonstrated ownership, accountability, learning agility, and willingness to work in an evolving AI landscape.

Exposure to Generative AI, LLMs, RAG, AI agents, agentic frameworks, or vector databases.

Experience in pharmaceutical, life sciences, healthcare, or commercial analytics is a plus, but not mandatory.