At a Glance
- Tasks: Lead data analytics for Microsoft AI's health team, driving insights and metrics for product development.
- Company: Join Microsoft AI, a leader in technology and healthcare innovation, dedicated to improving user health management.
- Benefits: Enjoy a dynamic work environment with opportunities for growth, collaboration, and cutting-edge technology.
- Why this job: Be part of a mission-driven team that values technology's role in health while tackling real-world challenges.
- Qualifications: Degree in Data Science or related field; experience in data analysis, A/B testing, and Python proficiency required.
- Other info: Microsoft promotes diversity and inclusion, welcoming applicants from all backgrounds.
The predicted salary is between 43200 - 72000 £ per year.
At Microsoft AI, 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.
The Data Analytics/Science Lead – Consumer Health role is an integral part of the Microsoft Health AI team; and will act as a data generalist bringing visibility to our product efforts. We’re looking for someone who thinks deeply about measurement and human-AI interactions.
Across all our hires, it’s important for colleagues to share our enthusiasm about the role of technology and AI in health and healthcare, but also appreciate the challenges and risks of delivering effective solutions in a complex and safety critical space. By design, we will remain a lean team (albeit within a much larger organization), and as such you will need to be action orientated, self-sufficient and actively help to cultivate and promote a positive team culture.
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.
- Drive new ways of instrumentation and measurement approach to evaluate new feature performance through experimentation.
- Enable A/B experimentation for new features.
- Hands-on analysis of large volumes of telemetry data using various algorithms and tools including your own.
- Articulate insights, storyboard with data and communicate to influence leadership and other key decision makers.
- Find a path to get things done despite roadblocks to get your work into the hands of users quickly and iteratively.
- Enjoy working in a fast-paced, design-driven, product development cycle.
Minimum Qualifications:
- Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results).
- 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.
- Proficiency in Python.
Preferred Qualifications:
- Experience working on product analytics to drive product improvements.
- Experience with prompt engineering and using LLMs. In particular, experience thinking about analytics in the context of conversations, and multi-turn unstructured data.
- Experience with Healthcare data or data taxonomies.
- Dedication to writing clean, maintainable, and well-documented code with a focus on application quality, performance, and security.
- 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.
- Passion for learning new technologies and staying up to date with industry trends, best practices, and emerging technologies in web development and AI.
- Ability to work in a fast-paced environment, manage multiple priorities, experiment quickly, and adapt to changing requirements and deadlines.
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.
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Data Analytics/Science Lead employer: Microsoft Corporation
Contact Detail:
Microsoft Corporation Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Analytics/Science Lead
✨Tip Number 1
Familiarize yourself with the latest trends in healthcare AI and data analytics. Understanding how technology is transforming health management will not only help you in interviews but also show your passion for the field.
✨Tip Number 2
Network with professionals in the healthcare AI space. Attend relevant meetups or webinars to connect with others who share your interests, and don’t hesitate to reach out to current employees at Microsoft to learn more about their experiences.
✨Tip Number 3
Prepare to discuss specific examples of your experience with A/B testing and data analysis. Be ready to articulate how you've used metrics to drive product improvements in past roles, as this aligns closely with the responsibilities of the position.
✨Tip Number 4
Showcase your ability to work in a fast-paced environment by sharing stories of how you've managed multiple priorities and adapted to changing requirements. This will demonstrate that you can thrive in the dynamic culture at Microsoft.
We think you need these skills to ace Data Analytics/Science Lead
Some tips for your application 🫡
Understand the Role: Take the time to thoroughly read the job description for the Data Analytics/Science Lead position. Understand the key responsibilities and qualifications required, especially focusing on metrics development, A/B testing, and data analysis.
Highlight Relevant Experience: In your application, emphasize your experience with data science, particularly in managing structured and unstructured data, developing algorithms, and executing large-scale A/B testing. Use specific examples to demonstrate your skills.
Showcase Your Technical Skills: Make sure to mention your proficiency in Python and any other relevant tools or technologies you have used in data analytics. Highlight any experience you have with healthcare data or product analytics, as this is a preferred qualification.
Communicate Your Passion: Express your enthusiasm for the role of technology and AI in health and healthcare. Share your dedication to learning new technologies and staying updated with industry trends, as well as your ability to work collaboratively with cross-functional teams.
How to prepare for a job interview at Microsoft Corporation
✨Show Your Passion for Health and AI
Make sure to express your enthusiasm for the intersection of technology, AI, and healthcare. Share examples of how you've used data science to improve health outcomes or enhance user experiences in previous roles.
✨Demonstrate Your Analytical Skills
Be prepared to discuss specific projects where you developed metrics, conducted A/B testing, or analyzed large datasets. Highlight your experience with Python and any relevant algorithms you've implemented.
✨Communicate Clearly and Effectively
Practice articulating complex technical concepts in a way that is understandable to both technical and non-technical stakeholders. This will be crucial when discussing insights and influencing decision-makers.
✨Emphasize Team Collaboration
Since the role requires working closely with cross-functional teams, share examples of how you've successfully collaborated with product managers, designers, and engineers in the past. Highlight your interpersonal skills and ability to foster a positive team culture.