Head of Data Science, AI Acceleration studio

Overview

We are hiring a Head of Data Science with broad experience and deep expertise in applying machine learning to real-world problems. You will develop and communicate hypotheses, analyses, results, ecosystem trends and ultimately innovative solutions to various stakeholders. You will work cross-functionally with several teams including engineering crews, product teams, and program managers.

As a part of Industry Solutions Engineering (ISE), at the AI Acceleration Studio we work closely with senior executives and cross-functional teams as we bring design, data science, and engineering to jointly develop cloud-based solutions that have high impact and can accelerate the organization. We work in collaboration with Microsoft product teams, partners, and open-source communities to empower our customers to do more. We pride ourselves on making contributions to open source and making our platforms easier to use.

In this role, you will be working with engineers and designers, while managing a data science group to apply your skills, perspectives, and creativity to trailblaze new ground and build first-of-a-kind AI solutions.

Industry Solutions Engineering (ISE) is part of Microsoft Industry Solutions, a global organization of over 16,000 strategic sellers, industry experts, elite engineers, and world-class architects, consultants, and delivery experts who work together to bring Microsoft’s mission of empowerment – and cutting-edge technology - to life for the world’s most influential customers.

The ISE team works directly with customers 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 engineers from your team and our customers’ teams to apply your skills, perspectives, and creativity to grow as engineers and help solve our customer challenges. 

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.

Watch this video to learn more about who we are and what we do: https://aka.ms/csevideo.

Responsibilities

People Management

Managers deliver success through empowerment and accountability by modeling, coaching, and caring.

• Model - Live our culture; Embody our values; Practice our leadership principles.
• Coach - Define team objectives and outcomes; Enable success across boundaries; Help the team adapt and learn.
• Care - Attract and retain great people; Know each individual’s capabilities and aspirations; Invest in the growth of others.

Business Understanding and Impact

• Lead data-science projects or teams to align with business needs and deliver value.

Data Preparation and Understanding

• Lead data acquisition and understanding efforts for engineering projects using various tools and techniques.

Modeling and Statistical Analysis

• Develop and apply ML frameworks and best practices for scalable and ethical AI solutions.

Evaluation

• Oversee review of data analysis and modeling techniques. Ensure selected modeling techniques are appropriate and aligned with desired project outcomes. Decide on next steps (e.g., deployment, further iterations, new projects).

Industry and Research Knowledge/Opportunity Identification

• Provide feedback, drive improvement, and share knowledge as a data science expert.

Business Management

• Lead ML and data-science partnerships and IP improvements where applicable.

Customer/Partner Orientation

• Provide customer-oriented insights and solutions by understanding the business, product, data, and customer perspective.

Other

• Embody our culture and values

Qualifications

Required Qualifications:

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 8+ years 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 10+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
• OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 12+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
• OR equivalent experience.
• 10+ years people-management experience, with a track record of building and developing successful data science teams.
• 12+ years customer-facing, global project-delivery experience, including exposure to international business development and complex partnership structures, demand-generation concepts, and presales.
• Demonstrated current or recent coding, debugging, and engineering skills in programming languages such as C++ , C# or Python.
• Expertise in deep learning and 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).
• Strong team-player, good communicator, embrace challenges, and keen to learn.
• Strong oral and written communication skills, with particular emphasis on customers and senior stakeholders.

Preferred Qualifications:

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 10+ years 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 12+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
• OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 15+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
• OR equivalent experience.
• 10+ years professional experience developing in C++, C#, or Python.
• Experience with ML frameworks (Pytorch, Tensorflow, etc.)
• Previous experience with Microsoft Azure

Experience with practical issues around AI deployments, including hardware (client and server), software (AI frameworks, MLOps and FMOps), data (data protection, privacy, sovereignty); and legal/regulatory (IP, explainability, bias, and safety).

Locations:

United Kingdom, Switzerland, Netherlands