Senior Data Scientist
Do you want to join us and apply machine learning to tackle difficult problems in biotechnology drug development? As an AI Scientist, you can play a pivotal role in a rapidly growing team analyzing and manipulating various types of biomedical datasets and generating the insights from our complex data that brings innovative medicines to patients.
About AstraZeneca in Gaithersburg, MD:
Our Gaithersburg, Maryland facility creates life-changing medicines for people around the world. This campus employs more than 3,500 experts in our field and is only a short drive from Washington, DC. This modern and vibrant scientific campus is the home of R&D and Oncology in the US. Here, we play host to some of the most cutting-edge technology and lab spaces, all designed to inspire collaboration and cross-functional science. We believe employees benefit from being challenged and inspired at work. We are dedicated to creating a culture of inclusion and collaboration.
The Gaithersburg site offers a variety of amenities to help boost productivity and help keep our employees happy and healthy. This includes a fitness center, employee healthcare clinic, electric vehicle charging stations, dry cleaning, full-service cafeteria and copy center. This is where you’ll find newly-designed, activity-based work spaces to suit a range of working styles while increasing collaboration between teams.
Summary of the group:
The Data Science and Modeling team within AstraZeneca’s Biopharmaceutical Development (BPD) group applies sophisticated algorithms and techniques to solve some of the hardest problems in the development of biological medicinal products. The team uses a blend of scientific, problem solving, and quantitative skills to develop and deliver ground breaking methods addressing critical problems in bioproduct development.
Our team of data scientists work right next to biotechnology scientists and operational teams, allowing them direct influence on the questions, the design of the corresponding studies and real time access to the resulting data. Biopharmaceutical Development has more than 20 years of experience with biotherapeutics, has brought more than 100 molecules to the clinic and has launched 6 new therapies. Together we seek to:
- Improve our understanding of disease and uncovering new targets
- Transform R&D processes
- Speed the design and delivery of new medicines for patients
Main Duties & Responsibilities:
- Develop, implement and support modelling solutions for the AI ecosystem for bioprocess optimization including integrating data from multiple different sources and modalities, as well as the application of classification, regression, clustering, image analysis, or graph theory and other specialist techniques
- Researching and developing predictive models and computational methods to guide decision-making within project parameters and established approaches
- Translate unstructured, business problems into the appropriate data problem, model and analytical solutions
- Perform AI research, including establishment of hypotheses that can be approached using computational methods and tools. May present or publish findings for conferences and in peer reviewed journals
- Build effective relationships with established range of stakeholders to ensure utilization and value of information resources and services. Clearly and objectively communicate results, as well as their associated uncertainties and limitations within agreed frameworks
- Develop, maintain and apply ongoing knowledge and awareness in trends, standard methodology and new developments in analytics and data science
Education & Experience Requirements:
Graduate Degree in mathematics, computer science, physics, statistics, engineering, or a related quantitative discipline.
- Knowledge of modern data science approaches, including unsupervised and supervised classification and regression algorithms. May also have expertise in advanced statistical modelling, or broader aspects of applied mathematics such as dynamical systems or optimization.
- Algorithm design, development, optimization, scaling and applications
- Data modeling experience with sequential data such as signals, sequences, and time series.
- Predictive modeling: Classification and Regression
- R, Python/Julia Programming experience, SQL Querying
- Stakeholder management and effective communication of the results and models
- Understanding and familiarity with deep learning algorithms for RNN, CNN, or reinforcement learning for sequential data modeling
- Recommendation systems
- CNN for Image analysis and processing
- AWS storage and services
- Excellent problem solving, written and verbal communication, business analysis, and consultancy skills
At AstraZeneca when we see an opportunity for change, we seize it and make it happen, because any opportunity no matter how small, can be the start of something big. Delivering life-changing medicines is about being entrepreneurial - finding those moments and recognising their potential. Join us on our journey of building a new kind of organisation to reset expectations of what a bio-pharmaceutical company can be. This means we’re opening new ways to work, pioneering cutting edge methods and bringing unexpected teams together. Interested? Come and join our journey.
So, what’s next!
Are you ready to bring new ideas and fresh thinking to the table? Brilliant! We have one seat available and we hope it’s yours.
Where can I find out more?
Check out our landing page for more information on our BPD group https://careers.astrazeneca.com/bpd
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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 authorisation and employment eligibility verification requirements.