National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

EMEA ML Practice - Sr. Data Science Manager

Databricks
London
1 month ago
Create job alert

CSQ326R68

Mission


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.


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

Related Jobs

View all jobs

Sr Data Science Manager, Professional Services

Senior Data Scientist

Data Scientist/ ML Engineer

Engineering Manager – AI/ML (Computer Vision Focus)

Data Scientist, AWS Industries

Senior Data Scientist

National AI Awards 2025

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Return-to-Work Pathways: Relaunch Your AI Career with Returnships, Flexible & Hybrid Roles

Stepping back into the workplace after a career break can feel like embarking on a whole new journey—especially in a cutting-edge field such as artificial intelligence (AI). For parents and carers, the challenge isn’t just refreshing your technical know-how but also securing a role that respects your family commitments. Fortunately, the UK’s tech sector now boasts a wealth of return-to-work programmes—from formal returnships to flexible and hybrid opportunities. These pathways are designed to bridge the gap, equipping you with refreshed skills, confidence and a supportive network. In this comprehensive guide, you’ll discover how to: Understand the booming demand for AI talent in the UK Leverage transferable skills honed during your break Overcome common re-entry challenges Build your AI skillset with targeted training Tap into returnship and re-entry programmes Find flexible, hybrid and full-time AI roles that suit your lifestyle Balance professional growth with caring responsibilities Master applications, interviews and networking Whether you’re returning after maternity leave, eldercare duties or another life chapter, this article will equip you with practical steps, resources and insider tips.

LinkedIn Profile Checklist for AI Jobs: 10 Tweaks That Triple Recruiter Views

In today’s fiercely competitive AI job market, simply having a LinkedIn profile isn’t enough. Recruiters and hiring managers routinely scout for top talent in machine learning, data science, natural language processing, computer vision and beyond—sometimes before roles are even posted. With hundreds of applicants vying for each role, you need a profile that’s optimised for search, speaks directly to AI-specific skills, and showcases measurable impact. By following this step-by-step LinkedIn for AI jobs checklist, you’ll make ten strategic tweaks that can triple recruiter views and position you as a leading AI professional. Whether you’re a fresh graduate aiming for your first AI position or a seasoned expert targeting a senior role, these actionable changes will ensure your profile stands out in feeds, search results and recruiter queues. Let’s dive in.

Part-Time Study Routes That Lead to AI Jobs: Evening Courses, Bootcamps & Online Masters

Artificial intelligence (AI) is reshaping industries at an unprecedented pace. From automating mundane tasks in finance to driving innovation in healthcare diagnostics, the demand for AI-skilled professionals is skyrocketing. In the United Kingdom alone, AI is forecast to deliver over £400 billion to the economy by 2030 and generate millions of new jobs across sectors. Yet, for many ambitious professionals, taking time away from work to upskill can feel like an impossible ask. Thankfully, part-time learning options have proliferated: evening courses, intensive bootcamps and flexible online master’s programmes empower you to learn AI while working. This comprehensive guide explores every route—from short tasters to deep-dive MScs—showcasing providers, course formats, funding options and practical tips. Whether you’re a career changer, a busy manager or a self-taught developer keen to go further, you’ll discover a pathway to fit your schedule, budget and goals.