Senior Data Scientist
Role details
Job location
Tech stack
Job description
Our dedicated Data Science team is at the forefront of revolutionizing pharma intelligence and how patients gain access to life-saving therapies. Armed with cutting-edge technology and a passion for innovation, we leverage the vast landscape of data to extract actionable insights that drive informed decision making.
Our unique collaborative approach fosters a dynamic synergy between data science, product development, pharmaceutical industry experts, and engineering. Our deep expertise in artificial intelligence, machine learning, and advanced statistical modelling, combined with our domain knowledge, enables us to deliver comprehensive solutions that empower our clients to stay ahead in a rapidly evolving industry. We have delivered multiple products live to customers, with many more in development., In this role as a Senior Data Scientist, you will:
- Collaborate with product partners and others to identify new opportunities to apply AI / ML to our content and products
- Conduct research and identify AI / ML algorithms and methods to solve specific business problems
- Implement rigorous testing and evaluation of potential solutions; review indicative results and proof-of-concepts with multi-disciplinary teams as part of customer-led product development
- Deploy your solutions as production-grade microservices in collaboration with engineering and DevOps teams
- Contribute towards common data science platforms and data assets
- Stay up-to-date, constantly learning about advances in the field, and deliver periodic presentations to internal teams on these developments
- All other duties, as assigned
As a senior-level scientist, you will primarily be responsible for one major release at a time with a high degree of individual ownership. While not all research leads to successful deployed systems, past successes have seen a general availability launch typically ~6 months from project start. Our solutions have used a wide range of approaches, including: agentic systems and model context protocol (MCP) servers, retrieval augmented generation (RAG), classical machine learning, knowledge graphs, and simply well-designed data transformations and business logic - our focus is on solving problems rather than the technology used.
Requirements
- Graduate degree in a STEM field such as Computer Science, Engineering, Statistics, or equivalent practical experience
- 5+ years of experience developing AI / ML applications and data driven solutions
- Excellent knowledge of Python and core data science libraries such as pandas, scikit-learn, LangChain, etc.
- Experience with LLMs, e.g. foundation model APIs, prompt engineering, retrieval augmented generation
- Substantial depth and breadth across state-of-the-art AI / ML techniques such as Generative AI, NLP, Deep Learning, etc.
- Understanding of CS fundamentals, computational complexity, and algorithm design
- Ability to engineer and deploy well-architected software packages
- Strong communication and stakeholder management skills, ability to independently own and execute a project holistically at a high level
- Experience mentoring junior team members, * Deep expertise in engineering agentic AI systems
- Knowledge of the healthcare / pharma domain and experience applying AI to healthcare data
- Experience with AWS, especially ECS, Bedrock, SageMaker, serverless compute and storage
- Ability to prototype PoC webapps with familiarity across the full stack
- Expert usage of AI coding tools and workflows
Benefits & conditions
- Medical and Prescription Drug Benefits
- Health Savings Accounts (HSA) or Flexible Spending Accounts (FSA)
- Dental & Vision Benefits
- Basic Life and AD&D Benefits
- 401k Retirement Plan with Company Match
- Company Paid Short & Long-Term Disability
- Paid Parental Leave
- Open Vacation Policy& Company Holidays, The expected base salary for this position ranges from $200,000 to $215,000. It is not typical for offers to be made at or near the top of the range. Salary offers are based on a wide range of factors including relevant skills, training, experience, education, and, where applicable, licensure or certifications obtained. Market and organizational factors are also considered. In addition to base salary and a competitive benefits package, successful candidates are eligible to receive a discretionary bonus.
