Business Data Analyst

Workable
London
1 month ago
Create job alert

Ometria is a Customer Data and Experience Platform built for retail marketers to be the fastest route to sustainable growth. Ometria helps marketers plan and launch their most profitable campaigns twice as fast, increasing their customer loyalty and CRM revenue with personalised marketing messages all throughout the customer journey.

Our platform combines the data unification and customer insight of a CDP with an experience platform, letting retail marketers easily and efficiently create experiences their customers love across email, mobile, on-site, social, direct mail and more.

Ometria is trusted by some of the fastest-growing retail brands in the world such as Brooklinen, Davines, Steve Madden, and Sephora.

We have a team of over 120 Ometrians based in North America and Europe. We have raised $75m from leading venture capital funds across the world such as Infravia Capital Partners, Octopus Ventures, Summit Action, Sonae IM and many others.

The role

We are looking for a Business Data Analyst to inform and support key stakeholders in interpreting and analysing data, identifying trends, and generating recommendations to guide strategic decisions.​ In this role, you will play a pivotal part of our continued success in the UK but also support our US expansion plans and help us win there.

As a Business Data Analyst, you will work in the Retail Strategy team, reporting to the Chief Customer Officer, and will collaborate with other client-facing teams such as Customer Success, Marketing, Sales, and with the senior management team to deliver data-driven insights.

You’ll play a key role in ensuring that our clients and prospects rightly perceive Ometria as the foremost data-driven Customer Data and Experience Platform platform.

Key outcomes

  • Lead the workstreams involving data extraction, transformation, analysis, visualisation for Ometria’s Architect 360 offering - our innovative, AI-driven consultancy solution, designed to uncover hidden revenue opportunities within a customer’s data - ensuring that both the retail intelligence team and the customer success team can deliver Architect 360 effectively, and contributing to this offering’s continuous improvement
  • Partner with our client-facing teams to extract, transform and present data on specific client projects to demonstrate that Ometria is the foremost retail-focused CDXP, prioritising the activities based on client urgency, importance and impact
  • Partner with internal-facing teams to extract insights that can drive decisions on our product or how we serve our clients
  • Collaborate with the product & engineering team to ensure our data architecture keeps improving to enable the level of analysis Ometria’s clients need

Key responsibilities

  • Be the subject matter expert when it comes to data in the Ometria platform: what is available, what it means, how to access and analyse it, potential constraints or limitations
  • Partner with the Retail Strategy team to design Ometria Architect 360 deliverables, and create and manage tools to enable the team to access the relevant data in a scalable manner
  • Translate high-level client requirements into specific data projects, and translate the outcomes and insights back into commercially meaningful language
  • Lead the provision of ad hoc data and insights to various parts of the business, utilising suitable tools such as python, SQL, spreadsheets, etc.
  • Represent the data analysis function (if required) in communication with clients, in collaboration with the Retail Strategy, Customer Success, Sales and Marketing teams.
  • Collaborate with the marketing team to identify data-driven stories within our datasets that can be turned into engaging content.

Requirements

Requirements

  • You have at least 3-4 years of experience as a business analyst or data analyst in a dynamic, fast-paced environment; retail focus preferred
  • You have experience extracting data from databases using SQL and analysing data using Python (NumPy, Pandas, etc.)
  • You have a bachelor degree in a quantitative subject
  • You are capable of acting as a trusted advisor when presenting data and insights to key stakeholders in multiple departments, especially those that are client-facing
  • You are able to see the bigger picture when looking at data and interpreting it from a commercial and pragmatic, result-oriented perspective
  • You have a proactive, inquisitive mindset when it comes to using data to identify business opportunities and insights
  • You are comfortable working with multiple key stakeholders across different departments within the business (e.g. Customer Success, Marketing, Sales, etc.), ensuring that they are up-to-date and at all times have all the information they need to manage their external stakeholders
  • You are able to communicate in a clear, concise and commercially-driven manner.
  • You can manage multiple priorities at the same time, and are comfortable switching to the activity that matters the most as priorities change
  • You are organised, disciplined and consistent in the way you manage your time, tools, data, insights, and outputs
  • You consider different approaches to solving a problem, and pick the one that is most pragmatic and effective to achieve the desired business outcomes

Benefits

  • 30 days holiday + 1 day on your birthday (plus bank holidays)
  • Health Insurance (Bupa)
  • Mental Health Support (Spill, Calm)
  • Cycle to work scheme
  • Enhanced Financial Benefits (Salary Sacrifice Pension, DIS, Income Protection)

The amazing people of Ometria are the core of our business. We believe in making it

awesome to be here for all Ometrians and place a continued focus on making Ometria

an inclusive, respectful and diverse environment.

We're an equal opportunity employer and all applicants will be considered for

employment without attention to ethnicity, age, religion, sexual orientation, gender

identity, family or parental status, national origin, veteran, neurodiversity status or

disability status.



Related Jobs

View all jobs

Business & Data Analyst

Business Data Analyst (Gloucestershire)

Business Data Analyst

Business Data Analyst

Senior Business Data Analyst

Data Analyst - Graduate

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Quantum-Enhanced AI in Data Science: Embracing the Next Frontier

Data science has undergone a staggering transformation in the past decade, evolving from a niche academic discipline into a linchpin of modern industry. Across every sector—finance, healthcare, retail, manufacturing—data scientists have become indispensable, leveraging statistical methods and machine learning to turn raw information into actionable insights. Yet as datasets grow ever larger and machine learning models become more computationally expensive, there are genuine questions about how far current methods can be pushed. Enter quantum computing, a nascent but promising technology grounded in the counterintuitive principles of quantum mechanics. Often dismissed just a few years ago as purely experimental, quantum computing is quickly gaining traction as prototypes evolve into cloud-accessible machines. When paired with artificial intelligence—particularly in the realm of data science—the results could be game-changing. From faster model training and complex optimisation to entirely new forms of data analysis, quantum-enhanced AI stands poised to disrupt established practices and create new opportunities. In this article, we will: Explore how data science has reached its current limits in certain areas, and why classical hardware might no longer suffice. Provide an accessible overview of quantum computing concepts and how they differ from classical systems. Examine the potential of quantum-enhanced AI to solve key data science challenges, from data wrangling to advanced machine learning. Highlight real-world applications, emerging job roles, and the skills you need to thrive in this new landscape. Offer actionable steps for data professionals eager to stay ahead of the curve in a rapidly evolving field. Whether you’re a practising data scientist, a student weighing up your future specialisations, or an executive curious about the next technological leap, read on. The quantum era may be closer than you think, and it promises to radically transform the very fabric of data science.

Data Science Jobs at Newly Funded UK Start-ups: Q3 2025 Investment Tracker

Data science has become an indispensable cornerstone of modern business, driving decisions across finance, healthcare, e-commerce, manufacturing, and beyond. As organisations scramble to capitalise on the insights their data can offer, data scientists and machine learning (ML) experts find themselves in ever-higher demand. In the UK, which has cultivated a robust ecosystem of tech innovation and academic excellence, data-driven start-ups continue to blossom—fuelled by venture capital, government grants, and a vibrant talent pool. In this Q3 2025 Investment Tracker, we delve into the newly funded UK start-ups making waves in data science. Beyond celebrating their funding milestones, we’ll explore the job opportunities these investments have created for aspiring and seasoned data scientists alike. Whether you’re interested in advanced analytics, NLP (Natural Language Processing), computer vision, or MLOps, these start-ups might just offer the career leap you’ve been waiting for.

Portfolio Projects That Get You Hired for Data Science Jobs (With Real GitHub Examples)

Data science is at the forefront of innovation, enabling organisations to turn vast amounts of data into actionable insights. Whether it’s building predictive models, performing exploratory analyses, or designing end-to-end machine learning solutions, data scientists are in high demand across every sector. But how can you stand out in a crowded job market? Alongside a solid CV, a well-curated data science portfolio often makes the difference between getting an interview and getting overlooked. In this comprehensive guide, we’ll explore: Why a data science portfolio is essential for job seekers. Selecting projects that align with your target data science roles. Real GitHub examples showcasing best practices. Actionable project ideas you can build right now. Best ways to present your projects and ensure recruiters can find them easily. By the end, you’ll be equipped to craft a compelling portfolio that proves your skills in a tangible way. And when you’re ready for your next career move, remember to upload your CV on DataScience-Jobs.co.uk so that your newly showcased work can be discovered by employers looking for exactly what you have to offer.