Senior Data Scientist

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.

Job Description

The Digital Health R&D Human-centered AI (HAI) 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 Senior Data Scientist to specialize in applying 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.

The Data Scientist will work closely with the Digital Health R&D subject matter experts, stakeholders and other team members to develop novel approaches that support the development of innovative products. Applicants should have a strong foundation in statistics, and experience with machine learning in a production environment.

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
Works with complex multimodal clinical datasets. Conducts analysis using data science and machine learning techniques.
Builds data and analysis pipelines to deliver clinical insights and reusable capabilities.
Researches and implements novel methods in optimization, machine learning, data analysis, data visualization.
Communicates results to technical and non-technical stakeholders at multiple levels.
Independently keeps own knowledge up to date and learns from senior team members, proposing appropriate training courses for personal development.
Collaborates in a multidisciplinary environment with world leading clinicians, data scientists, biological experts, statisticians and IT professionals.
Education, Qualifications, Skills and Experience

Essential
M.Sc. degree in rigorous quantitative science (such as mathematics, computer science, engineering) or have demonstrated an outstanding track-record of industry experience (2+ years) with the desired data science methodologies with a B.Sc. in a relevant field (such as mathematics, computer science, engineering).
Demonstrated experience with and a sound understanding of a variety of statistical and machine learning methods and standard statistical/ML development practices.
Practical software development skills in standard data science tools: Python, Code versioning (bitbucket/git), UNIX skills, familiarity working in cloud environment (AWS preferred)
Experience developing machine learning first products such as timeseries analysis, multi-objective optimization, forecasting, behavioral analysis
Strong communication and teamwork skills
Desirable
Ph.D./M.Sc. degree in rigorous quantitative science (such as mathematics, computer science, engineering)
Interactive data visualization (interactive dashboards w/ DASH, plotly, etc.,)
Advanced experience with Kubernetes and machine learning product architecture
Advanced statistical and machine learning models such as hierarchical mixed bayesian models, transformer-based NLP models, reinforcement learning, deep learning models that span CNN/RNN/LSTM, GNNs, constrained optimization, state-of-the-art timeseries & forecasting models
Experience in data-led solution delivery and software lifecycle development practices including Agile/Scrum, Waterfall, DevOps and/or CI/CD.
ML Ops experience: model tracking, model governance, multiple models in different production contexts
Communication, business analysis, and consultancy
Experience within the pharmaceutical industry
Date Posted 11-jul-2023

Closing Date 21-jul-2023

AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.
AstraZeneca

Fecha de publicación: 13/07/2023