At a Glance
- Tasks: Lead innovative data science solutions in real-world evidence generation for drug development.
- Company: Join GSK, a global biopharma leader dedicated to advancing health.
- Benefits: Competitive salary, bonuses, comprehensive health benefits, and generous leave policies.
- Other info: Collaborative culture with opportunities for mentorship and professional growth.
- Why this job: Make a real impact on healthcare by pioneering cutting-edge data science technologies.
- Qualifications: PhD in Data Science or related field with extensive experience in healthcare.
The Senior Director Data Science Innovation Lead will pioneer transformative solutions in real-world evidence generation in the Real-World Data, Measurement, and Analytics (RWDMA) organization, supporting the entire drug development life cycle from early development to late-phase clinical trials and post-approval market access and reimbursement. Leveraging the latest advancements in data sciences, such as multimodal AI, generative AI, knowledge graphs, causal AI and agentic AI, the Data Science Innovation Lead will develop and optimize statistical methodologies in comparative effectiveness analyses, precision medicine, predictive modelling, and evidence synthesis. In addition, the Innovation Lead will support AI-driven automation tools and deployment of intelligent systems for more efficient data processing and automate complex data analyses and QC processes, thereby accelerating development timelines while ensuring compliance with regulatory standards.
Key Responsibilities
- Data Science Strategy & Leadership: Align RWDMA Data Science initiatives with RWD organizational drug development goals, regulatory requirements (e.g., FDA, EMA), and payer expectations, ensuring strategic impact and compliance, particularly in RWD analytics. Lead RWDMA Data Science through a matrix organization, collaborating with biostatisticians, clinical and other subject matter experts, and regulatory specialists to lead innovative applications of Data Science in RWE generation and embed Data Science into RWD workflows to improve efficiency of data processing and analysis.
- Innovative Applications of Data Science in RWE Generation: Design customized Data Science models tailored to specific RWD analytic applications, including: Comparative Effectiveness, Precision Medicine, Predictive Modelling, and Evidence Synthesis.
- Automation & Process Optimization: Automate coding, including clinical coding and patient identification, and quality control (QC) processes using AI-driven anomaly detection and pattern recognition. Develop Natural Language Processing (NLP) tools to automate the creation, review, and validation of analytic plans and protocols.
- Data Strategy: In alignment with DDF and D3 initiatives and the RWDSP team, assess the gaps in data needs in RWD and use potential Data Science applications to inform data strategy.
- Collaboration & Thought Leadership: Mentor team members in advanced Data Science methodologies, fostering a culture of innovation and technical excellence across real world biostatistics, digital measurement, and other focus areas.
Qualifications
- PhD in Data Science, Biostatistics, Computer Science, or a related field.
- 15+ years in healthcare and life sciences, with significant exposure to pharmaceutical and/or medical device industries.
- 10+ years in clinical development or RWE generation within regulated environments, including hands-on leadership of Data Science projects.
- Demonstrated success in deploying DataOps, ModelOps, or MLOps pipelines in cloud platforms (e.g., Azure, AWS).
Technical Skills:
- Expertise in statistical modelling, AI and machine learning techniques.
- Proficiency in generative AI and the technical stack and tools.
- Strong programming skills in Python, R, TensorFlow, PyTorch, and experience with cloud tools.
- Familiarity with multi-domain real-world data.
Achievements:
- Proven track record of innovation in Data Science applications for healthcare.
- Experience navigating ethical, privacy, and regulatory challenges in AI-driven healthcare solutions.
Senior Director, Data Science Innovation Lead in Slough employer: Gsk
GSK is an exceptional employer, offering a dynamic work environment in Waltham, Massachusetts, where innovation meets purpose. With a strong commitment to employee growth, GSK provides comprehensive benefits, including health care, retirement plans, and generous leave policies, fostering a culture that prioritises collaboration and accountability. As a leader in biopharma, GSK empowers its employees to make a meaningful impact on global health while advancing their careers in cutting-edge data science and analytics.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Director, Data Science Innovation Lead in Slough
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We think you need these skills to ace Senior Director, Data Science Innovation Lead in Slough
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Craft a Tailored Cover Letter:For a full-time role at Gsk, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Gsk. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Gsk
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Gsk!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
