Principal Data Scientist

As a Principal Data Scientist, you will own end-to-end delivery of strategic data science projects and partner with customers and internal teams to design and implement advanced analytics and AI solutions that create measurable business impact. This role blends deep, hands-on technical knowledge with consulting and stakeholder engagement, enabling you to influence decisions and guide adoption of data-driven strategies.

Leverage data science and business domain knowledge to improve business performance, evaluate project plans, communicate business goals, and share insights with business stakeholders

Lead the design and development of Data Science and broader AI solutions of a team of data scientists and engineers.

Engage with business stakeholders to bring them along with business performance improvement with data and AI

Apprentice and generate the next generation of data scientists and actively participate and lead their mentoring

Acquire, prepare, and explore data through querying, visualisation, reporting techniques, and collaboration with other teams, ensuring data integrity.

Apply machine learning and statistical analysis to develop models, train, optimise, and evaluate them, and communicate findings to stakeholders.

Test, review, and improve models by analysing performance, incorporating feedback, and contributing to the review process.

Write and debug efficient and scalable code while collaborating with engineering teams and integrate data models into customer systems.

Collaborate with customers and Microsoft teams to define business needs, create roadmaps for performance improvements, and influence stakeholders using storytelling and visual tools to drive solution value.

Uphold ethical standards by emphasizing Responsible AI principles in guiding stakeholders throughout the process.

Focus on customer needs and perspectives to promote adoption and build trust.

Develop and execute tailored solutions by overcoming obstacles and leveraging in-depth knowledge of Microsoft products.

Maintain transparency about data limitations to set realistic expectations and ensure accountability.

Proactively seeks new knowledge and adapts to new trends, technical solutions, and patterns that will improve the availability, reliability, efficiency, observability, and perf