Senior Data Scientist
MicrosoftAbout the role
Do you enjoy solving problems, looking at problems through a different lens, and working closely with customers to innovate new solutions to complex problems? Do you jump with excitement at the opportunity to identify trends and provide unique business solutions? Do you want to join a team where learning about a new technology or solution is part of our work every day? Then, come join us!
The Industry Solutions Engineering (ISE) team is a global engineering organization that works directly with customers looking to leverage the latest technologies to address their toughest challenges.
We work closely with our customers’ engineers to jointly develop code for cloud-based solutions that can accelerate their organization. We work in collaboration with Microsoft product teams, partners, and open-source communities to empower our customers to do more with the cloud. 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.
As Senior Data Scientist, you will help drive high-impact engineering projects with our customers and their partners, transforming their missions using AI and other cloud-based solutions and services. Data scientists have data management and expertise in developing statistical techniques to analyze data and find patterns. You will be part of a cross-functional team of software engineers, data scientists, technical program managers, and designers who work side-by-side with high-impact and strategic customers and their engineers to build innovative solutions.
As part of our team, you will thrive in working with a variety of technologies, not just Microsoft technology. You will solve exciting business problems, contribute to open source, and collaborate with Microsoft product teams.
Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
Responsibilities
Data Acquisition & Preparation- Lead efforts to gather project-specific data, build usable datasets for modeling, and enhance internal best practices for data collection. Engage with customers to ensure data integrity and alignment with ethical standards.
- Assess and improve team models, champion modeling best practices, and develop scalable operational models. Innovate new evaluation techniques and conduct rigorous reviews of analysis methods.
- Stay current with industry trends and technologies to inform strategic decisions. Write extensible, multi-feature code and refine debugging skills to support robust development.
Experimentation Leadership & Cross-Functional Collaboration
- Champion A/B testing and experimental design to validate product impact, while leveraging tools like SQL, R, and Python for analysis. Lead and grow a high-performing data science team, and build partnerships across product and business units to deliver data-informed solutions.
- Define and align business and customer strategy goals, collaborate across teams to uncover new opportunities, and maintain a customer-first approach to deliver realistic, value-driven solutions.
You will embody our culture and values.
Qualifications
Required/minimum qualifications
- Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managin
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