Sr Data Science Manager Professional Services

Databricks
London
8 months ago
Applications closed

Related Jobs

View all jobs

Senior/Lead Health Data Scientist – Statistical Genetics

Senior Data Scientist, Surfline Coastal Intelligence

Senior Data Scientist

Data Scientist

Data Scientist

Data Scientist

CSQ326R68

Mission

The Machine Learning (ML) Practice team is a highly specialized collaborative customerfacing ML team at Databricks. We deliver professional services (PS) engagements to help our customers build scale and productionize the most cuttingedge ML and GenAI applications. We work crossfunctionally to shape longterm 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 worldclass 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 worldclass 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 crossfunctionally 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 handson 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 productiongrade machine learning deployments on AWS Azure or GCP
  • Passion for collaboration lifelong 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 customerfacing role


Required Experience:

Manager


Key Skills
Close Protection,Credit Control,Customer Service,Government,Analytics
Employment Type :Full Time
Experience:years
Vacancy:1

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.

Maths for AI Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are a software engineer, data scientist or analyst looking to move into AI or you are a UK undergraduate or postgraduate in computer science, maths, engineering or a related subject applying for AI roles, the maths can feel like the biggest barrier. Job descriptions say “strong maths” or “solid fundamentals” but rarely spell out what that means day to day. The good news is you do not need a full maths degree worth of theory to start applying. For most UK roles like Machine Learning Engineer, AI Engineer, Data Scientist, Applied Scientist, NLP Engineer or Computer Vision Engineer, the maths you actually use again & again is concentrated in a handful of topics: Linear algebra essentials Probability & statistics for uncertainty & evaluation Calculus essentials for gradients & backprop Optimisation basics for training & tuning A small amount of discrete maths for practical reasoning This guide turns vague requirements into a clear checklist, a 6-week learning plan & portfolio projects that prove you can translate maths into working code.

Neurodiversity in AI Careers: Turning Different Thinking into a Superpower

The AI industry moves quickly, breaks rules & rewards people who see the world differently. That makes it a natural home for many neurodivergent people – including those with ADHD, autism & dyslexia. If you’re neurodivergent & considering a career in artificial intelligence, you might have been told your brain is “too much”, “too scattered” or “too different” for a technical field. In reality, many of the strengths that come with ADHD, autism & dyslexia map beautifully onto AI work – from spotting patterns in data to creative problem-solving & deep focus. This guide is written for AI job seekers in the UK. We’ll explore: What neurodiversity means in an AI context How ADHD, autism & dyslexia strengths match specific AI roles Practical workplace adjustments you can ask for under UK law How to talk about your neurodivergence during applications & interviews By the end, you’ll have a clearer picture of where you might thrive in AI – & how to set yourself up for success.

AI Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we head into 2026, the AI hiring market in the UK is going through one of its biggest shake-ups yet. Economic conditions are still tight, some employers are cutting headcount, & AI itself is automating whole chunks of work. At the same time, demand for strong AI talent is still rising, salaries for in-demand skills remain high, & new roles are emerging around AI safety, governance & automation. Whether you are an AI job seeker planning your next move or a recruiter trying to build teams in a volatile market, understanding the key AI hiring trends for 2026 will help you stay ahead. This guide breaks down the most important trends to watch, what they mean in practice, & how to adapt – with practical actions for both candidates & hiring teams.