Senior Data Scientist – AI & Advanced Analytics
Location: Seattle, Washington, United States
Employment Type: Full-time
Industry: Life Sciences / Pharmaceuticals / Technology
About the Role
A global life sciences organisation is seeking a Senior Data Scientist to join an AI-focused innovation team. This is a hands-on individual contributor role at the intersection of data science, applied AI, machine learning and AI product development.
The successful candidate will help transform complex scientific and business challenges into measurable AI solutions, working closely with AI engineers, data engineers, product teams, cloud engineers and subject-matter experts.
The role will involve developing and evaluating AI systems across areas including R&D, commercialisation, manufacturing and corporate functions, with a strong focus on experimentation, analytical rigour and measurable business impact.
Key Responsibilities
Translate ambiguous scientific and business problems into measurable AI hypotheses, success metrics and experimental plans.
Develop data science prototypes using Python, SQL, notebooks, APIs and cloud-based data services.
Design and execute experiments to evaluate AI products, models, retrieval systems and agentic workflows.
Develop analytical features, embeddings, classifiers, ranking and scoring methods, recommendation logic, simulations and optimisation approaches where appropriate.
Design evaluation frameworks for LLM, RAG and agentic AI applications, including evaluation datasets, rubrics, structured output validation and error taxonomies.
Assess model and agent performance, including quality, uncertainty, calibration, bias, hallucination risk, traceability and fitness for purpose.
Work with data engineering teams to develop reliable datasets, retrieval corpora, metadata and feature pipelines.
Define KPIs and measurement strategies covering AI adoption, user behaviour, workflow efficiency, scientific utility and business value.
Apply statistical modelling, experimental design, causal inference and other analytical methods to distinguish meaningful signals from noise.
Create clear analyses, visualisations and narratives that communicate model behaviour, limitations and opportunities to technical and non-technical stakeholders.
Contribute to responsible AI, security, quality, privacy and governance initiatives.
Develop reusable notebooks, evaluation frameworks, analytical templates and data science patterns.
Participate in technical reviews, design discussions and collaborative problem-solving across engineering and product teams.
Use AI-assisted coding and development tools while maintaining strong analytical and scientific standards.
Coach colleagues on data science, evaluation design, measurement strategy and evidence-based decision-making.
Required Experience & Qualifications
Bachelor's degree or higher in Data Science, Statistics, Computer Science, Engineering, Bioinformatics, Computational Biology, Applied Mathematics or a related scientific discipline.
5+ years of experience in data science, machine learning, applied AI, analytics, computational science or a related technical field.
Strong proficiency in Python and SQL, with experience using data science libraries such as pandas, NumPy, scikit-learn, PyTorch, TensorFlow or similar.
Experience applying machine learning, statistics, NLP, information retrieval, experimentation or decision science to real-world products or business/scientific workflows.
Practical experience with LLM applications, RAG, agentic AI, prompt and evaluation design, structured outputs and model quality assessment.
Familiarity with cloud data and AI services, particularly AWS, including services such as S3, Athena, RDS/PostgreSQL, OpenSearch, SageMaker or Bedrock.
Experience with evaluation frameworks, hallucination-risk assessment, causal inference, simulation, optimisation or recommendation methodologies.
Understanding of vector databases, embeddings, knowledge graphs, metadata strategies and data quality practices.
Familiarity with lightweight data and AI prototyping tools such as Streamlit.
Ability to communicate quantitative findings, assumptions, limitations and recommendations clearly to both technical and non-technical audiences.
Experience using AI-assisted development tools such as Claude Code, Codex, Gemini CLI, GitHub Copilot or similar technologies.
Comfortable working in agile, cross-functional teams and adapting analytical approaches as new evidence emerges.
What You'll Work On
This role offers the opportunity to work with modern AI and data technologies, including large language models, retrieval-augmented generation, agentic workflows, vector databases, knowledge graphs and cloud-based analytics platforms.
You'll help build practical AI solutions while establishing the evaluation, measurement and governance practices needed to ensure those solutions are reliable, explainable and valuable.
Compensation
US salary range: approximately $151,280–$183,319, depending on location and experience.
Additional incentive compensation and benefits may be available.
Work Environment
The position operates within a collaborative, agile environment alongside data scientists, engineers, product leaders and subject-matter experts. The role may involve working across multiple business functions and supporting the development and adoption of emerging AI capabilities.

Senior Data Scientist

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