Head of Data Analytics

Ohme
London
7 months ago
Applications closed

Related Jobs

View all jobs

Head of Data Analytics

Head of Data Analytics & AI

Senior Data Engineer

Head of Data Architecture

Head of Data Architecture

Senior Claims Data Analyst

Join to apply for the Head of Data Analytics role at Ohme

Join to apply for the Head of Data Analytics role at Ohme

Get AI-powered advice on this job and more exclusive features.

Ohme is on a mission to accelerate the global transition to clean, affordable energy. We do that by serving as an integrated hardware and software smart-grid platform, focused on the residential EV charging market.

The worlds of energy, transport and artificial intelligence are colliding and Ohme is at the heart of this new era. By using technology and data integrations to connect cars, chargers, people, energy providers and more, Ohme has a powerful platform that puts the consumer at the core.

Ohme has been selling its chargers to consumers since mid 2019 and has had exponential growth since. We are now operating in multiple countries and have partnerships with the likes of VW, Mercedes, Octopus Energy, and other innovative brands.

We are scaling up the business and are building out the team for rapid growth. If you’re interested joining a fast-growing cleantech venture on a data and AI-first journey to speed up the global transition to clean, affordable energy, read on!

The Head of Data Analytics will lead the development and implementation of data analytics strategies that align with Ohme’s strategic goals. This role involves working closely with stakeholders to identify key data-driven opportunities and using analytics and new AI solutions to enhance decision-making processes.

You will be exploring and implementing new tools to support Ohme’s vision to be a data-centric and “AI first” business. We are looking for a candidate who is willing to understand the depth and breadth of Ohme’s data, offering guidance and support to the team. They should be involved in both leadership and hands-on tasks.

Here’s What You’d Be Doing

  • Lead the Data Analytics team to deliver actionable insights and reliable reporting in a fast-paced environment with competing stakeholders and priorities.
  • Staying at the forefront of data analytics and AI trends, identifying opportunities and building to leverage cutting-edge technologies and methodologies
  • Collaborate with various areas of the business to understand their data needs and implement solutions that enhance productivity and efficiency.
  • Clearly communicating complex data insights to other areas of the business and senior leadership, enabling data-driven decisions at all levels
  • Driving the advancement of analytical capabilities across the group with a focus on self-serve, experimentation, and reporting
  • Championing data-driven decision making across the organisation, ensuring that insights are translated into actionable recommendations for business impact

What We’re Looking For

  • Demonstrable experience in designing and delivering a compelling Data vision and engaging across organisational domains to ensure alignment and support. You have developed and led a Data strategy, taking full ownership rather than only being in the delivery.
  • Extensive commercial experience with the ability to align data and AI initiatives with overall business objectives
  • Hands-on Analytics background with strong technical skills in Python, SQL, and cloud computing platforms - this is essential!
  • Proven experience in a senior leadership role in a fast-paced high growth scale-up.
  • A track record of data modelling, and applying advanced analytics, data systems and tools, machine learning, and AI, to drive business growth.
  • Exceptional communication skills with the ability to translate complex technical concepts for diverse stakeholders
  • Advanced degree in Computer Science, Data Science, Statistics, or a related quantitative fields
  • Experience with best-in-class data visualisation and business intelligence tools
  • Deep knowledge of agile methodologies and their application in data and analytics projects
  • Proactive thinker with a strong sense of ownership and the ability to think critically and independently.

You’ll get to work in a fast-paced and rapidly growing scale-up with global ambitions that is cutting edge, passionate about sustainability and seeks to make the world a better place.

Our benefits:

  • Competitive salary and bonus
  • Hybrid office
  • Private Health Insurance
  • Aegon Pension Scheme
  • Life Assurance Scheme with death in service benefit of 4x salary
  • Income Protection Scheme for long term illness

Ohme is an equal opportunity employer. Diversity, Equity and Inclusion are at the heart of what we do and we encourage a culture where everyone can be themselves at work. We actively seek out a diverse range of talent and our policies ensure that every job application and employee is treated fairly, with equal opportunity to succeed and to feel included.Seniority level

  • Seniority levelNot Applicable

Employment type

  • Employment typeFull-time

Job function

  • IndustriesFood and Beverage Services

Referrals increase your chances of interviewing at Ohme by 2x

Sign in to set job alerts for “Head of Analytics” roles.

London, England, United Kingdom 2 weeks ago

City Of London, England, United Kingdom £90,000.00-£90,000.00 5 days ago

London, England, United Kingdom 5 days ago

London, England, United Kingdom 1 week ago

London, England, United Kingdom 1 week ago

London, England, United Kingdom 1 week ago

London, England, United Kingdom 2 days ago

Greater London, England, United Kingdom 2 weeks ago

Surbiton, England, United Kingdom 3 days ago

London, England, United Kingdom 2 days ago

London, England, United Kingdom 2 weeks ago

London, England, United Kingdom 1 month ago

London, England, United Kingdom 2 weeks ago

Head of Insights - UK- Fixed Term Contract

London, England, United Kingdom 1 week ago

London, England, United Kingdom 3 weeks ago

Head of Enterprise Data Science and AI Platforms

London, England, United Kingdom 2 weeks ago

Director, Insights, Strategy & Analytics – International Productions

London, England, United Kingdom 1 week ago

Head of Data - Analytics Engineering & InsightsDirector of Quantitative Modelling & Analytics (Consultancy)Head of EMEA Reinsurance Reporting & Analytics

London, England, United Kingdom 2 weeks ago

London, England, United Kingdom 3 months ago

London, England, United Kingdom 1 month ago

We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.


#J-18808-Ljbffr

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.

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.

The Skills Gap in Data Science Jobs: What Universities Aren’t Teaching

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.