At a Glance
- Tasks: Build data foundations for an innovative health AI companion and optimise data pipelines.
- Company: Join Microsoft AI, a leader in technology and innovation.
- Benefits: Competitive salary, inclusive culture, and opportunities for professional growth.
- Why this job: Shape the future of health tech and make a real difference in people's lives.
- Qualifications: Degree in relevant field or equivalent experience; strong data science skills required.
- Other info: Fast-paced environment with a focus on collaboration and continuous improvement.
The predicted salary is between 36000 - 60000 £ per year.
Overview At Microsoft AI, we are inventing an AI Companion for everyone – an AI designed with real personality and emotional intelligence that’s always in your corner. Defined by effortless communication, extraordinary capabilities, and a new level of connection and support, we want Copilot to define the next wave of technology. This is a rare opportunity to be a part of a team crafting something that challenges everything we know about software and consumer products. Our health team is on a mission to help millions of users better understand and proactively manage their health and wellbeing. We’re responsible for ensuring that Microsoft AI’s models and services are useful, trusted and safe across diverse customer health journeys.
Role We’re looking for a deeply technical and mission-driven Data Scientist - Health AI to build the data foundations powering our health AI companion. You’ll architect, scale, and optimize the pipelines, datasets, and metrics frameworks that help us understand user behavior, evaluate model performance, and measure health impact. This role sits at the intersection of product, engineering, analytics, and applied AI—translating raw signals into insights that shape product decisions and ensure our health AI systems are safe, effective, and grounded in evidence.
Key Responsibilities
- Develop metrics for the healthcare category of Copilot usage and quality
- Drive product insights, opportunity analysis, and track metrics to support efforts across Microsoft Copilot.
- Enable A/B testing and other experimentation for new features
- Design, build, and maintain high-quality data pipelines and models that power analytics, dashboards, and product experimentation across health AI experiences
- Partner with product and clinical counterparts to define source-of-truth datasets and standardized metrics for user engagement, safety, and health outcome evaluation
- Drive continuous improvement in data quality, discoverability, and observability
- Contribute to shaping data infrastructure strategy and tooling to support next-generation health AI systems
- Enjoy working in a fast-paced, design-driven, product development cycle & embody our Culture and Values
Required Qualifications
- Bachelor’s or Master’s degree in Mathematics, Statistics, Data Science, Computer Science, Engineering, or related field OR equivalent experience.
- Experience in leveraging complex data, applied data science, developing sophisticated algorithms, executing large-scale A/B testing, and possessing extensive product knowledge.
- Experience with metrics creation, predicting trend analysis, measuring traffic patterns, and assessing experimentation results.
- Experience working with Python for data processing, analytics, or pipeline orchestration
- Experience applying data science in a scaled consumer products environment
- Demonstrated interpersonal skills and ability to work closely with cross-functional teams, including product managers, designers, and other engineers, while clearly communicating complex technical concepts to both technical and non-technical stakeholders
Preferred Qualifications
- Experience working in healthcare or digital health data environments; Ideally, familiarity with typical health data taxonomies, governance, data privacy, and compliance standards (HIPAA & PHI handling, De-identification standards, etc.)
- Exposure to large language model (LLM) or generative AI systems, particularly in analytics or model evaluation contexts
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled. Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances.
If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.
Data Science Lead,Health AI in London employer: Microsoft Corporation
Contact Detail:
Microsoft Corporation Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Science Lead,Health AI in London
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at events. A friendly chat can lead to opportunities you might not find on job boards.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects and data science work. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by practising common data science questions and case studies. We recommend doing mock interviews with friends or using online platforms to get comfortable.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive!
We think you need these skills to ace Data Science Lead,Health AI in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Science Lead role. Highlight your experience with data pipelines, metrics creation, and any relevant projects that showcase your skills in health AI. We want to see how your background aligns with our mission!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about health AI and how you can contribute to our team. Be sure to mention specific experiences that relate to the key responsibilities outlined in the job description.
Showcase Your Technical Skills: Don’t forget to highlight your technical skills, especially in Python and data science methodologies. We’re looking for someone who can dive deep into data, so make sure to include any relevant tools or frameworks you’ve worked with.
Apply Through Our Website: We encourage you to apply through our website for the best chance of being noticed. It’s super easy, and you’ll be able to keep track of your application status. Plus, we love seeing applications come directly from our site!
How to prepare for a job interview at Microsoft Corporation
✨Know Your Data Science Fundamentals
Brush up on your core data science concepts, especially those related to healthcare. Be ready to discuss how you’ve applied metrics creation and A/B testing in past projects, as these are crucial for the role.
✨Showcase Your Technical Skills
Prepare to demonstrate your proficiency in Python and any relevant data processing tools. You might be asked to solve a problem or explain your approach to building data pipelines, so have some examples ready.
✨Understand the Product and Its Impact
Familiarise yourself with Microsoft Copilot and its health AI applications. Think about how your work can enhance user engagement and safety, and be prepared to share insights on how data can drive product decisions.
✨Communicate Clearly and Collaboratively
Since this role involves working with cross-functional teams, practice explaining complex technical concepts in simple terms. Highlight your interpersonal skills and give examples of successful collaborations in your previous roles.