Principle Data Scientist
Location: Cambridge (UK), Gothenburg (Sweden)
Salary and Benefits: Competitive
The AI and Analytics team within AstraZeneca’s R&D Data Science and AI (DS&AI) group uses sophisticated algorithms and techniques to resolve some of the hardest problems in the discovery and development of new medicines.
The team uses a blend of scientific, problem solving, and quantitative skills to develop and deliver ground breaking methods addressing critical problems in our R&D environment.
Our team of data scientists work right next to our other scientists and operational teams, allowing them to be close to the questions that matter and work on a broad range of the most promising opportunities quickly.
The Data Science & AI team collaborates across R&D to drive innovation through DS and AI. 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
Do you want to join us and apply machine learning to tackle difficult problems in drug development? As a Data Science Director, you can play a pivotal role in a rapidly growing team analysing and manipulating various types of biomedical datasets and generating the insights from our complex data that brings innovative medicines to patients faster.
In this role you will join a rapidly growing team analysing and manipulating various types of biomedical datasets and generating the insights from our complex data that brings innovative medicines to patients faster.
You will apply your expertise in machine learning, quantitative data analysis and artificial intelligence to develop innovative data science solutions in clinical drug development. To achieve this, you will provide and develop new technologies/methods and work in a highly multidisciplinary environment with world leading clinicians, data scientists, biological specialists, statisticians and IT professionals.
We work on a flexible and varied portfolio of challenges that could include, but are not limited to:
- Enabling Digital Health by developing an ecosystem of capabilities around remote monitoring, telemedicine, medical and wearable devices.
- Researching and developing algorithms on high-frequency, near real-time data generated from wearable devices such as activity monitors, continuous glucose monitors, wearable ECG, SpO2, spirometry, audio and video.
- Researching and developing end-to-end automation and inference pipelines using state-of-the-art serverless architectures in cloud platforms such as AWS.
- Modelling patient behaviour and the patient journey to improve patient engagement, reduce drop-out and boost health outcomes.
These challenges will require you to:
- Lead, advise on, investigate the feasibility of, and deliver data science solutions and ideas that drive value to AstraZeneca
- Apply a range of data science methodologies, developing novel data science solutions where off-the-shelf methodologies do not fit
- Translate unstructured, complex business problems into the appropriate data problem, model and analytical solutions
- Develop, implement and maintain tools and algorithms in a manner which meets regulatory and evidential requirements
- Clearly and objectively communicate results, as well as their associated uncertainties and limitations
- Constructively collaborate with a diverse set of users (global functions and local marketing companies) and partners enabling effective consensus, conflict resolution and alignment to project goals
- Review and develop working practices to ensure that data science work is delivered to robust quality standards
- PhD in mathematics, computer science, statistics, physics, engineering or a related computational discipline. Applicants with a PhD in a biomedical discipline who also have proven experience in data science and high proficiency in predictive modeling are encouraged to apply.
- High proficiency and proven track record of researching, designing, coding and delivering high impact data-driven insights through machine learning.
- High proficiency in hands-on computer programming in Python, R or similar programming language.
- High proficiency in exploratory data analysis, data profiling and feature engineering on large, structured and unstructured datasets.
- Excellent written and verbal communication, business analysis, and consultancy skills
- Customer focus - dedicated to meeting the expectations and requirements of internal and external customers
- Integrity and trust -- unwavering commitment to "doing the right thing"
- A passion to apply machine learning and other data science techniques to tackle difficult problems in drug development, clinical trials and related biomedical domains of value for AstraZeneca.
- Experience in novel methods development and application
- Understanding of life sciences, with a preference for clinical drug development and the pharmaceutical environment
- Experience in data-driven solution delivery and software lifecycle development practices including Agile/Scrum, Waterfall, DevOps and/or CI/CD.
- Experience in AWS and building serverless data pipelines and inference pipelines.
- Multiple published papers and/or patents, contribution to open source projects
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
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.