Do you enjoy solving problems, looking at problems through a different lens, and working closely with healthcare customers to innovate new solutions to complex problems with a focus on Generative AI?

 

The Industry Solutions Engineering (ISE) team is a global engineering organization that works directly with Microsoft’s most strategic Healthcare and Life Sciences customers who are looking to leverage the latest technologies to address their toughest challenges. We develop solutions side-by-side with our customers through collaborative innovation to solve their challenges. This work involves the development of broadly applicable, high-impact solution patterns and open-source software assets that contribute to the Microsoft platform. In this role, you will be working with data scientists, program managers and engineers from your team and our customers’ teams to apply your skills, perspectives, and creativity to grow as engineers and help solve our customers’ toughest challenges.

 

We are looking for a Principal Data Scientist with deep expertise in machine learning, AI, and a track record of developing production ML/AI/Gen-AI solutions that deliver business impact. You will work cross-functionally with several teams including data scientists, engineering crews, product teams, and program management to deploy business solutions for Microsoft clients in the Healthcare and Life Sciences sector.

 

Our team prides itself on embracing a growth mindset, inspiring excellence, and encouraging everyone to share their unique viewpoints and be their authentic selves. Join us and help create life-changing innovations that impact billions around the world!

Responsibilities

Business Understanding and Impact

Leverages subject matter expertise to analyze problems and issues to uncover, manage, and/or mitigate factors that can influence final outcomes for customers. Partners with customer teams to drive strategy and recommend improvements. Establishes, applies, and teaches standards and best practices.

Modeling and Statistical Analysis

Generalizes machine learning (ML) solutions into repeatable frameworks (e.g., modules, packages, general-purpose software) for others to use. Exemplifies and enforces team standards related to bias, privacy, and ethics. Develops operational models that run at scale. Identifies new customer opportunities for driving transformative customer solutions with ML modeling. Incorporates best practices for ML modeling with consideration for artificial intelligence (AI) ethics.

Industry and Research Knowledge/Opportunity Identification

Tracks advances in industry and academia, identifies relevant state-of-the-art research, and adapts algorithms and/or techniques to drive innovation and develop new solutions. Serves as a subject matter expert and role model for customers and less experienced data scientists. Identifies strategy opportunities.

Coding and Debugging

Independently writes efficient, readable, extensible code/model that spans multiple features/solutions. Contributes to the code/model review process by providing feedback and suggestions for implementation and improvement. Develops expertise in proper modeling, coding, and/or debugging techniques. Leads a project team in the gathering, integrating, and interpreting of data/information from multiple sources.

Business Management

Defines business-strategy goals, customer-strategy goals, and solution-strategy goals. Partners with internal and customer teams to identify and explore opportunities for the application of machine learning (ML) and other data-science tools. Works collaboratively across disciplines.

Customer/Partner Orientation

Commits to a customer-oriented focus by acknowledging customer needs and perspectives, validating customer perspectives, focusing on broader customer organization/context, and serving as a trusted advisor. Identifies opportunities and adds valuable insight by incorporating an understanding of the business, product/service functionality, data sources, methodologies to reframe problems, and the customer perspective. Leads the discussion with customers and offers pragmatic solutions that are feasible given their data limitations.

Qualifications

Required Qualifications:

• 10+ years of data-science experience (e.g., managing structured and unstructured data, applying statistical techniques, and reporting results), out of which 8 years of experience in industry.
• Degree in Engineering, Computer Science, Mathematics, Statistics, or related field
• Expertise in deep learning models with hands-on experience applying them in real-world scenarios.
• 3+ years customer-facing, project-delivery experience, professional services, and/or consulting experience.
  
  

 

Preferred Qualifications

• Experience working as part of geographically dispersed, diverse, and virtual teams
• Enjoy travel and are comfortable with travel up to 25% (once per quarter)
• Demonstrated ability to work with customers and collaborate across company boundaries
• 12+ years of data-science experience (e.g., managing structured and unstructured data, applying statistical techniques, and reporting results), out of which 10 years of experience in industry.
• Expertise in generative AI models with hands-on experience applying them in real-world scenarios.
• Knowledge of advancements and emerging research in foundation models, including large language models (LLMs).
  
  

 

Our team prides itself on embracing a growth mindset, inspiring excellence, and encouraging everyone to share their unique viewpoints and be their authentic selves. Join us and help create life-changing innovations that impact billions around the world!

 

At Microsoft, we are seeking people who have a passion for the positive impact technology can have on communities and for making a difference in the world. Within ISE, you will find a wide range of backgrounds, perspectives, personal and cultural experiences which are vital to our success with our customers. It’s an informal and flexible work environment and you’ll be welcome to work in the way that best enables you to get your job done.

 

We invest in your health, wellness, and financial future by offering a competitive package including a wide range of benefits built around your personal needs and those close to you.

 

#ISEngineering

Microsoft is an equal opportunity employer. Consistent with applicable law, 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 and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.