Sr Data Science Manager, Professional Services

The Machine Learning (ML) Practice team is a highly specialized, collaborative customer-facing ML team at Databricks. We deliver professional services (PS) engagements to help our customers build, scale, and productionize the most cutting-edge ML and GenAI applications. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations, as well as support internal subject matter expert (SME) teams.

We are looking for a world-class Sr. Manager to lead and grow our EMEA ML Practice. You will report directly to the AVP of Professional Services in EMEA and dotted line to our ML PS Global Leader. This role can be remote in Europe, but a preference is for candidates to be near a major office location such as London and Amsterdam.

The impact you will have:

• Lead and build a world-class ML + AI practice including hiring, onboarding and scaling of the team across EMEA.
• Develop relationships with key customers and partners, scope engagements, and manage escalations to ensure customer success.
• Align with the Field Engineering team and Sales Leaders in EMEA (and Global ML practice leadership) on key priorities for ML Services in the region.
• Lead strategic PS ML initiatives, practice development, and processes.
• Create opportunities for team members to collaborate cross-functionally with R&D to define priorities and influence the product roadmap.
• Scale knowledge and best practices across the wider Professional Services team.
• Own OKRs for revenue and utilization, with a focus on driving customer outcomes and Databricks consumption.
• Raise awareness and be a thought leader in the market by speaking at Databricks and other key ML events.
• Lead Databricks cultural values by example and champion the Databricks brand.

What we look for:

• Extensive experience managing, hiring, and building a team of motivated data scientists/ML engineers, including establishing programs and processes.
• Deep hands-on technical understanding of data science, ML, GenAI and the latest trends.
• While managers do not directly deliver customer engagements, we expect that candidates have related past technical experience that allows them to scope engagements and understand issues that arise in project delivery.
• Experience building production-grade machine learning deployments on AWS, Azure, or GCP.
• Passion for collaboration, life-long learning, and driving business value through ML.
• Company first focus and collaborative individuals - we work better when we work together.
• Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience (Preferred).
• Experience working with Databricks and Apache Spark (Preferred).
• Experience working in a customer-facing role.

About Databricks:

Databricks is the data and AI company. More than 10,000 organizations worldwide - including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 - rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark, Delta Lake and MLflow.

Benefits:

At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region, please visit mybenefitsnow.com/databricks.

Our Commitment to Diversity and Inclusion:

At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards.

Compliance:

If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.