Principal Data Scientist

at  Microsoft

Are you an experienced Data Scientist, and you love what you do? Would you like to be a part of a global customer facing Team focussed on solving complex, real-world business problems? Would you like to be a part of a worldclass community of technical leaders, highly specialised in their disciplines and working together as one to bring the best practices of Artificial Intelligence, Machine learning, Engineering and Architecture to world’s largest enterprise customers?
The Industry Solutions Delivery (ISD) Engineering & Architecture Group (EAG) is a global engineering consulting organisation that supports our most complex and leading-edge customer engagements in improving their business performance with the power of Data & AI. EAG develops approaches, innovative solutions, and engineering standards to set our delivery teams and customers up for long-lasting success. We are committed to Responsible AI, and we help our customers build and operate ethical, transparent and trustworthy AI solutions.
We are hiring a Principal Data Scientist with deep experience in advanced statistical data analysis, machine learning and artificial intelligence.
Our team embraces a continuous learning and growth mindset, encourages diverse viewpoints and relentless collaboration. We value personal and cultural experiences and strive for excellence. We offer a flexible work environment to help you succeed in creating transformative and responsible AI solutions that positively impact economy and people worldwide.

PREFFERED QUALIFICATIONS:

The ideal candidate excels in leading complex projects, designing scalable solutions, and applying advanced techniques to solve business challenges, demonstrates strong coding, problem-solving, and communication skills, clear understanding on the latest industry wide development and can act as role model apprenticing and growing our people and community.
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

• 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 scienstis 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.