Lead Data Scientist

Norstella is a premier and critical global life sciences data and AI solutions provider dedicated to improving patient access to life-saving therapies. Norstella supports pharmaceutical and biotech companies across the full drug development lifecycle — from pipeline to patient. Our mission is simple: to help our clients bring therapies to market faster and more efficiently, ultimately impacting patient lives.

Norstella unites market-leading brands - Citeline, Evaluate, MMIT, Panalgo, Skipta and The Dedham Group and delivers must-have answers and insights, leveraging AI, for critical strategic, clinical, and commercial decision-making. We help our clients:

• Accelerate the drug development cycle
• Assess competition and bring the right drugs to market
• Make data driven commercial and financial decisions
• Match and recruit patients for clinical trials
• Identify and address barriers to therapies

The Team

In this role as a Generative AI Lead Scientist you will report into the Head of Data Science, within Norstella. Your role will be to work with a dedicated group of data scientists and developers to use LLMs and related technologies to design and build products which will help answer complex customer questions directly, with citations and sources. We have a multi-functional team consisting of pharmaceutical industry experts, R&D, data engineering and data scientists to rapidly prototype using both our existing and newly acquired datasets across the pharmaceutical life cycle.

Scope of the Role

In this role as a Generative AI Lead Scientist you will:

• Work with our Product leadership within Norstella to define and shape new offerings using Generative AI
• Manage a team of data scientists and developers to provide Generative AI-enabled microservices to the front end dev team
• Manage a roadmap of Generative AI work, mixing new product development and enhancements to existing services
• Define reference architectures suitable to answer complex questions, including via code interpreting, LLM tool use and leveraging secondary data science models
• Coach and train a team of data scientists and developers to use these architectures
• Stay up-to-date, constantly learning about advances in the field, and deliver periodic presentations to the data science team on these developments
• Perform other duties, as assigned

How You’ll Succeed

Ultimately our goal is to smooth patient access to life-saving therapies. You will work with R&D pharma specialists to understand a problem which is hindering developing and releasing effective new pharma products which we believe we can help with. After understanding the problem you will conceptualise potential solutions; this will involve breaking down the problem into individual steps, and identifying which of them can be solved with available LLMs and other algorithms. Finally, an overall solution can be packaged together with multiple models chained together, mixed with classical logic and business rules.

After conceiving potential solution(s), you will define a set of projects for the data scientists and python developers to implement your solution as a proof-of-concept. You will deliver indicative results from your PoC into datasets for exploration by the broader multi-functional team. You will also perform code reviews with the data science team to examine their implementation and consider ways of strengthening the final codebase and methodology.

After iterating the design with the multi-functional team as part of customer-led product development, you might convert your prototype into a full product. This will involve productionising code from you and the team to a high standard, containerisation, and deployment of the algorithm, usually as an API in AWS SageMaker, or for smaller pieces Lambdas which invoke models via API. Over time you may revisit this product, re-evaluate its performance, and redesign/improve as required.

Essential Requirements

• Degree at Masters level or better in a STEM field such as Maths, Physics, Computer Science, Engineering, or equivalent practical experience
• Leadership experience, line managing data scientists or other highly specialised professionals
• Excellent communication skills when working with a broader development and product team
• Knowledge of Scrum, Kanban, and other Agile methodologies, as well as breaking down tasks into Jira tickets
• Proven experience using LLMs and prompt engineering inside applications to solve problems not tractable with older techniques
• Excellent knowledge of python and core data science libraries including Pandas, NumPy and other similar libraries

Nice to have

• Experience with AWS especially in relation to ML workflows with SageMaker, serverless compute and storage such as S3 and Snowflake
• Knowledge of the pharmaceutical industry, in particular the stages of pharmaceutical product development
• Ability to rapidly prototype new product ideas with a basic familiarity across the full stack, webapp to database
• Experience using external APIs in a production context

Benefits

• 25 days annual leave, 4 days for volunteering and a personal day
• Flexible working and flextime policies
• 5% pension match
• Group Life Assurance (100% employer funded)
• Group Income Protection (100% employer funded)
• Other voluntary benefits such as: Dental, Cash Plan, PMI Excess Cover, Health Screening & Critical Illness
• Maternity, Paternity & Adoption leave

Evaluate is an equal opportunities employer and do not discriminate on the grounds of gender, sexual orientation, marital or civil partner status, pregnancy or maternity, gender reassignment, race, colour, nationality, ethnic or national origin, religion or belief, disability or age. Our ethos is to respect and value people’s differences, to help everyone achieve more at work as well as in their personal lives so that they feel proud of the part they play in our success. Evaluate operates a zero tolerance policy to any form of discrimination, abuse or harassment.