Senior Data Scientist
Job Description
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? The Industry Solutions Engineering (ISE) team is a global engineering organization that works side-by-side with customers, on a per-project basis, to collaboratively innovate custom solutions to solve their challenging business problems; from inception to production. We develop broadly applicable, high-impact solution patterns and open-source software assets in collaboration with Microsoft product teams, partners, and open-source communities. This role will be primarily working with customers from the Retail & Consumer Goods industries. We are hiring a Data Scientist to build and deploy AI systems at scale as part of a cross-functional team—working on projects spanning computer vision, NLP, recommendation systems, predictive analytics, and generative AI. You'll analyse complex datasets, design experiments to validate hypotheses, and establish metrics linking technical outcomes to business impact. Working alongside engineers and technical program managers, you'll architect end-to-end AI solutions, develop production-ready ML pipelines, and contribute to scalable infrastructure serving millions of users while implementing MLOps practices at enterprise scale. The job title says "Data Scientist", but if you consider yourself an "AI/ML Engineer" this is still for you! 🔥 Microsoft’s mission is to empower every person and every organization on the planet to achieve more. Our team prides itself on embracing a growth mindset, innovating to empower others, and collaborating 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.
Locations
- Amsterdam, Noord-Holland, Netherlands, Amsterdam, Noord-Holland, Netherlands
Salary
Salary not disclosed
Required Qualifications
- Doctorate OR Master's Degree OR Bachelor's 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) (degree)
- Enjoy travel and are comfortable with travel up to 25% (degree)
- Customer-facing project-delivery experience. (degree)
- Experience working as part of geographically dispersed, diverse, and virtual teams (degree)
Responsibilities
- Business Understanding and Impact Leads data-science projects or teams to align with business needs and deliver value. Data Preparation and Understanding Leads data acquisition and understanding efforts for engineering projects using various tools and techniques. Modelling and Statistical Analysis Develops and applies ML frameworks and best practices for scalable and ethical solutions. Evaluation Oversees review of data analysis and modelling techniques. Ensures selected modelling techniques are appropriate and align with desired project outcomes. Decides on next steps (e.g., deployment, further iterations, new projects). Industry and Research Knowledge/Opportunity Identification Provides feedback, drives improvement, and shares knowledge as a data science expert. Coding and Debugging Writes and debugs code for complex projects and leads solution development. Business Management Leads ML and data-science partnerships and IP improvement. Customer/Partner Orientation Provides customer-oriented insights and solutions by understanding the business, product, data, and customer perspective.
- Leads data-science projects or teams to align with business needs and deliver value.
- Leads data acquisition and understanding efforts for engineering projects using various tools and techniques.
- Develops and applies ML frameworks and best practices for scalable and ethical solutions.
- Oversees review of data analysis and modelling techniques. Ensures selected modelling techniques are appropriate and align with desired project outcomes. Decides on next steps (e.g., deployment, further iterations, new projects).
- Provides feedback, drives improvement, and shares knowledge as a data science expert.
- Writes and debugs code for complex projects and leads solution development.
- Leads ML and data-science partnerships and IP improvement.
- Provides customer-oriented insights and solutions by understanding the business, product, data, and customer perspective.
- Other · Embody our culture and values
Travel Requirements
3 days / week in-office
