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kwiff

Data Scientist

London
Posted about 13 hours ago
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London - Chiswick (Hybrid pattern)

About kwiff

We aren't gambling as you know it. We’re a proprietary tech platform redefining the experience with a bold, player-first approach. Our signature feature, Supercharging, randomly boosts odds, cashouts and casino sessions, creating genuine moments of surprise and delight for our users. ⚡

We’re looking for a Data Scientist to develop data science solutions that deliver measurable business impact across the organisation. Working within the Data team, you’ll use advanced analytics, machine learning and data engineering techniques to solve business problems, supporting projects from initial concept through to production deployment. You’ll collaborate closely with commercial stakeholders to understand their challenges and translate them into scalable, data-driven solutions, while contributing to the continued development of our data science capability.

Key responsibilities & opportunities

  • Build and deploy machine learning models, taking solutions from initial ideation through to production deployment and ongoing optimisation.
  • Design, develop and maintain scalable data models, ETL pipelines and data workflows that support analytics and machine learning initiatives.
  • Analyse large and complex datasets to identify trends, patterns and opportunities, communicating insights in a clear, commercially impactful way.
  • Act as the organisation's subject matter expert for data-related queries, providing technical guidance and influencing data-driven decision making.
  • Monitor, maintain and continuously improve production models, ensuring reliability, performance, scalability and proactive issue resolution.
  • Collaborate with cross-functional teams to translate business problems into robust data science solutions that deliver measurable value.
  • Apply appropriate statistical analysis, experimentation and machine learning techniques to solve complex business challenges.
  • Contribute to the continuous improvement of data science practices, tooling and engineering standards across the team.
  • Work autonomously to identify opportunities, prioritise work and deliver high-quality solutions while collaborating effectively with colleagues and stakeholders.
  • Continuously develop technical expertise, staying up to date with advances in data science, machine learning and data engineering, and sharing knowledge across the team.

Reasons to use Rodeo

I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?

Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.

Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.

Start with a chat, not a search bar

Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.

P

Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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It searches the market for you

Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.

Why you're a good match

You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Strong

Experience fit

Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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Strong

Only hits

No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.

Essential skills

  • A degree in a STEM subject, ideally at Master’s level
  • Experience with SQL and Python
  • Familiarity with machine learning concepts and their practical application
  • Experience in cleaning, structuring, analysing, and visualising data from multiple sources
  • Experience developing cloud-based machine learning solutions
  • Familiarity with Git/GitHub
  • Ability to communicate complex data science concepts to non-technical audiences, building credibility and trust while influencing stakeholders
  • Excellent communication and presentation skills

Bonus skills

  • Experience delivering data science projects end-to-end in a commercial environment
  • Experience with recommender systems
  • Familiarity with the e-gaming industry (sports betting, casino, etc.)

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Benefits and Perks

  • Private Healthcare – Comprehensive medical insurance through Vitality Health.
  • Life Insurance – Coverage through Yulife for added peace of mind.
  • Bonus potential – Quarterly bonuses based on company achievements.
  • Weekly lunch - Enjoy lunch as a team on Fridays
  • Wellbeing Allowance – Spend on gym memberships or other wellness activities.
  • Sustainable Commuting – Cycle to Work schemes on offer.
  • Parental Support – Nursery schemes to reduce monthly fees.
  • Long Service Rewards – Exciting travel rewards for dedication after five years of service.
  • Learning Budget – Financial support for role-specific training to level up your skills.
  • Team Socials & Activities – Regular events, plus office perks like ping pong, darts, and PlayStation.
  • Hybrid Working Model – Spend three days a week working in our Chiswick office and two days at home.

At kwiff, we don’t just follow trends. We create them. From unlimited betting options to surprise wins and slick user journeys, we’re building a product that players love. Join us and help design the future of betting.

kwiff is an equal opportunity employer. We value diversity and are committed to creating an inclusive environment for all employees.

We aim for equity at all three stages of the recruitment process. Please let us know if there’s anything we can do to make the process more accessible to you.

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Skills

SQL
Python
Machine Learning
Data Engineering
ETL Pipelines
Statistical Analysis
Data Visualization
Cloud-based Machine Learning
Git
GitHub
Data Modeling
Experimentation
Recommender Systems

Location

London, England, United Kingdom

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