Director of Data Science

At AstraZeneca, we work together to deliver innovative medicines to patients across global boundaries. We make an impact and find solutions to challenges. We do this with integrity, even in the most difficult situations, because we are committed to doing the right thing.

The Digital Health R&D Human-centered AI Team aims to transform the patient experience and clinical trial process. Our solutions make a difference to the lives of our patients.

The team is looking for a Director of Data Science to specialize in and lead the development of innovative machine learning methods to augment decision making in clinical trial planning, monitoring and execution. This role will sit within the Enterprise Products team which aims to optimize clinical trial processes to ensure that the trial designed and developed is optimal for the patient population, drug target, and trial endpoints. The team also support the monitoring of the portfolio with forecasting and advanced analytics to provide operational insight.

Examples of projects the team works on include machine learning models for predicting and monitoring various aspects of clinical trials such as patient recruitment and trial duration, optimization of trial design from site selection to patient experience and much more

**Typical Accountabilities**
- Leads projects with hands-on data science, analysis, or mathematical modeling. Translates analysis results into business, product, or process recommendations.
- Coaches junior data scientists, and ensures both development of internal resources and recruitment of external talent to develop the capabilities of the team.
- Identifies opportunities for the wider team, frames challenges, and structures complex analytical solutions.
- Provides advanced data science expertise to AstraZeneca projects and recommends data science solutions.
- Engages non-technical stakeholders to interpret complex business needs and propose tangible technical solutions.
- Defines the analytical direction of projects and influences the direction of engineering teams in cross-functional collaborations.
- Lead regular code reviews with teams to ensure quality delivery.
- Independently keeps own knowledge up to date and learns from senior team members, proposing appropriate training courses for personal development.
- Represents team at internal and external venues.
- Collaborates in a multidisciplinary environment with world leading clinicians, data scientists, biological experts, statisticians and IT professionals.

**Education, Qualifications, Skills and Experience**

**Essential**
- 5-10 years of industry experience with an outstanding track-record of delivering a portfolio of end to end data science projects in an industry setting
- Practical software development skills in standard data science tools: Python, Agile, Code code versioning (bitbucket/git), UNIX skills, familiarity working in cloud environment (AWS preferred)
- Demonstrated experience of leading a team of talented data scientists
- Experience developing machine learning products involving techniques such as timeseries analysis, forecasting, optimization etc
- Communication, business analysis, and consultancy; ability to present compelling cases to stakeholders and operate dynamically to identify solutions

**Desirable**
- Ph.D. degree in rigorous quantitative science (such as mathematics, computer science, engineering) or M.Sc with analytics experience in industry.
- 10+ years of experience within the pharmaceutical industry with extensive knowledge of clinical trial process (all phases) and associated regulatory activities.
- ML Ops experience: model tracking, model governance, multiple models in different production contexts
- Advanced machine learning models: transformer-based NLP models, reinforcement learning, machine learning models for optimization, GNNs, state-of-the-art timeseries & forecasting models
- devOps/sysOps skills including Kubernetes and experience managing infrastructure as code in CI/CD pipelines