Data Analyst

Genie Ventures
Cambridge
1 week ago
Create job alert

Job Title: Data Analyst Company: Genie Shopping Ltd Department: Genie Shopping Network (Product & Innovation) Location: Flexible - Distributed with use of Cambridge office and occasional travel Working Hours: Full Time 37.5 hours per week with flexible working arrangements Salary Range: £36,575 - £39,623


Who is Genie Shopping?

Genie Shopping is a UK-based, high-growth performance marketing business operating through the affiliate channel and CSS ecosystem. As a certified Google CSS Premium Partner, we work with retail giants like Boots, eBay, Frasers, B&Q, Three, and Lookfantastic, serving over 57 billion ad impressions to users across our network. We differentiate ourselves through our managed CSS CPA model and our technical scale. We don’t act as a traditional CSS; we act as a performance partner. Alongside our self-managed SaaS offering, our core revenue comes from our CPA model, which means our success is directly aligned with our clients’. We are a driving force in the industry, leading the conversation through education, sponsorship, and active event contribution. This approach has led to huge success, doubling our growth in 2024 and setting new records in 2025. We are a certified Great Place to Work with a remote‑first setup. Our environment is small (~20 people) but ambitious. We value: Autonomy: We hire people who want to own their output. If you love solving complex problems and implementing your own ideas, you will thrive here. Connection: We prioritise culture over geography. We get together for proper team socials every quarter – think punting, cocktail making, and go‑karting, to ensure we stay connected as people, not just colleagues.


The team

The team is remotely based, but has fluidity in meeting in‑person for client meetings, industry events, strategy days and team socials. There are requirements to travel to Cambridge around once a month, with London (or other UK locations) once a month on average.


What is the role?

As a Data Analyst at Genie Shopping, you will play a crucial role in our continued growth and success within the performance marketing landscape. In this role, you will analyse affiliate marketing data to track key commercial and performance metrics, verify data accuracy, and ensure this is reflected in our systems. Your responsibilities will include structuring reports, extracting data, and telling stories using the data to make recommendations and provide actionable insights to optimise our strategies. You’ll also support strategic initiatives across teams, enable data‑driven decision‑making, and empower teams with self‑serve data. You will have the ability to create and maintain data sources, views and workbooks within Tableau, building on the existing infrastructure to visualise data for the team.


What you'll do

  • Data Quality Assurance: Conduct regular audits of our affiliate network transactional data to identify and resolve discrepancies, ensuring data integrity and reliability for reporting and analysis.
  • Retailer Performance Analysis: Analyse and identify critical factors influencing retailer performance, collaborate with cross‑functional teams to facilitate data‑informed decision‑making, and develop self‑service data solutions.
  • Project Support: Conduct ad‑hoc data analyses and generate reports as needed to address specific business projects or new initiatives.
  • Business Reporting: Improve and innovate the way we report key performance across regular reporting periods like daily, weekly and monthly snapshots in Slack.
  • Documentation: Maintain clear and concise documentation of data processes, reports, and methodologies to facilitate knowledge sharing and consistency.
  • Automation: Identify opportunities to automate data processes and reporting to improve efficiency and reduce manual effort.
  • Collaboration on Data Infrastructure: Work closely with the development team to improve data collection, storage, and management processes, suggesting enhancements to the data infrastructure to support better business reporting and insights.

Experience (Required)

Skills & Experience required



  • Proven experience in data analysis, including data extraction, cleaning, standardisation, and preparation from diverse sources using tools like Excel or BI platforms.
  • Solid understanding of data modelling and relational database concepts.

Experience (Desirable)

  • Proficiency in SQL for data querying and database table manipulation.
  • Hands‑on experience with developing and maintaining production‑ready dashboards using visualisation tools.
  • Experience with affiliate tracking platforms and performance marketing data.
  • Awareness of AI and machine learning techniques for data analysis and insight generation.

Skills (Required)

  • Proven ability to design, develop, and maintain complex Tableau dashboards and reports, leveraging advanced features to derive actionable insights.
  • Excellent analytical and numerical skills.
  • Demonstrated ability to extract actionable insights, identify patterns, and evaluate business opportunities and risks from complex datasets.
  • Exceptional written and verbal communication abilities, with the capacity to clearly explain technical data findings to diverse, non‑technical stakeholders.

Skills (Desirable)

  • Knowledge of affiliate marketing strategies and performance optimisation.
  • Previous work experience in e‑commerce analytics environments.
  • Understanding of Fivetran’s capabilities and its role in streamlining data pipelines.

What We Offer

  • Remote Working Allowance – We pay all Genies £126 per month WFH allowance.
  • Flexible Working – We provide flexibility in working options and work in a distributed team model.
  • 25 Days Annual Leave + Bank Holidays.
  • Enhanced Absence and Family Leave Policies.
  • Workplace Pension – Your 4 % employee contribution is matched by Genie via salary exchange.
  • Employee Referral Scheme – A bonus payment if we hire someone you recommend.
  • Electric Car Scheme – Allows you to lease an electric car through salary exchange, giving savings on Tax and NI.
  • Cycle to Work Scheme – The Cycle2Work Scheme allows you to buy a new bike for commuting to work, spreading the cost over 12 months via salary exchange.
  • Genie Academy – Our in‑house training helps develop talented people into world‑class digital marketers. Courses cover all aspects of the business.
  • Quarterly Social Events – We all get an afternoon off each quarter to attend a staff social. Events range from bowling and punting to cocktail making and quizzes.
  • Access to Spill – Professional therapist sessions.
  • Wellness Activities – Workshops and support sessions cover everything from crafting, exercise, posture and staying fit in the workplace through to managing both stress and financial wellbeing.
  • Wellbeing Perks – Paid eye tests, contribution towards glasses for DSE use and a yearly flu jab reimbursement.
  • Geniversaries – Work anniversary awards give gratitude to Genies for their dedication and commitment to the business.

We look forward to receiving your application!


Diversity, Equity & Inclusion

Genie Ventures is committed to creating a diverse, equitable and inclusive experience for our Genies and clients, in turn fostering a safe and happy workplace where everyone can be their authentic selves and thrive. We strive to build a team that reflects the diversity of the community we work in and encourage applications from traditionally underrepresented groups. If we can make this easier through accommodation in the recruitment process, please let us know via .


#J-18808-Ljbffr

Related Jobs

View all jobs

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Data Analyst

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 Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.