Quantitative Analyst - Cricket

Smartodds
City of London
3 days ago
Create job alert

We have a fantastic new opportunity to join our team at Smartodds as a Cricket Quantitative Analyst. Based in North London, Smartodds provides in-depth research and analysis on sporting events around the world, supported by world-class, bespoke software platforms. We are proud of our collaborative and dynamic culture, grounded in our core values of Boldness, Open-mindedness, Ownership, and Togetherness. We are a supportive and collaborative team - our environment is open, inclusive, and focused on doing great work together.


About the role

As a member of the Quant Team, you will join an exciting environment, predicting outcomes of professional sports on behalf of our clients. We focus on football, baseball, basketball, cricket, tennis, American football, ice hockey, horseracing and golf.


In this role, you will join our current team of cricket quant analysts developing statistical models primarily for cricket, while also supporting research into other sports, as well as investigating how our predictions can be leveraged to improve profitability and the overall commercial performance.


Furthermore, you will play a key role in developing and supporting the reliable production of high-quality predictions for our clients. We highly value the personal development of our team members and you will therefore be allotted dedicated time to improve your skills and gain the necessary experience that will enable you to progress into more senior roles.


You’ll have plenty of autonomy to execute your models from idea to code to validation to (hopefully) deployment, integrating your well documented and tested code into our internal libraries to help in prediction for at least one of the above sports.


The atmosphere is a collaborative academic one with peer reviews, research talks, and the opportunity for further education. Unlike academia though, the market is there to give immediate feedback on how good your model is. This makes the job challenging but also very exciting.


While we are open to applications from anyone who meets the minimum requirements, we would be especially keen to hear from applicants with more substantial research experience for this particular role.


Key Responsibilities

  • Contribute to identifying promising research directions; ensure research is carried out to the highest standard.
  • Develop cricket predictive models for both pre-match and in-play.
  • Contribute to discussions and efforts to identify weaknesses and potential improvements in existing models across all sports.
  • Support Smartodds' clients in their pricing tasks by developing, maintaining and supporting the mathematical libraries behind our range of tools and models and software that delivers model predictions into production.
  • Perform statistical analysis of datasets, testing well-defined hypotheses and effectively communicating results to the various stakeholders, including Smartodds' clients.
  • Attend at least one event to support your professional development as a sports quant analyst on an annual basis: conferences, courses, meet-ups, networking events; in‑person or remotely; on sports, statistics, machine learning, gambling, etc.

Skills & Experience
Required

  • MSc in Statistics or a related field (e.g., Data Science or Mathematics), or another field (such as Computer Science, Engineering, Finance, etc) with some experience in statistics.
  • PhD or equivalent in statistics (or related area) or 3+ years of work experience in a relevant role, e.g. sports quantitative analyst for a betting syndicate or a bookmaker.
  • Extensive experience of probabilistic and statistical modelling.
  • Strong programming skills in one high level language such as R or Python.
  • Demonstrated passion for working in sports modelling, evidenced by personal projects, MSc project in a related area or statistical analyses of sports or teams.
  • Ability to communicate results to those with and without specialist knowledge.
  • Ability to work in the UK.

Preferred

  • A strong interest in cricket demonstrated by previous attempts to model outcomes or analyse data.
  • Good understanding of sports betting markets.
  • Experience with and/or knowledge of Bayesian models, state‑space models, filtering and smoothing, computational statistics and approximate inference methods.
  • Experience with and/or knowledge of machine and statistical learning, deep neural networks, feature engineering, reinforcement learning, dynamic optimisation and optimal control.
  • Experience with automated trading systems.
  • Strong software development foundations.
  • Experience with any additional programming languages (such as C++ or Julia).
  • Familiarity with database technologies, e.g., SQL, MongoDB, Redis, Postgres.
  • Experience with version control, code reviews and merge requests.

What you can expect in return – Our Benefits

From Day One



  • 30 days holiday (in addition to bank and public holidays)
  • In‑house chef*
  • In‑house masseuse*
  • Team sporting events
  • 25% discount on Brentford Football Club merchandise
  • Cycle to work scheme
  • Employee Assistance Programme
  • Interest‑free travel season ticket loan
  • Offsite trips

*Available on selected days


After 3 Months



  • Pension – Employer Contribution starting at 5.5%, and employee starting at 2.5%
  • Income protection – 75% of salary (subject to terms and conditions)

After Probation



  • Private Medical Insurance – including coverage of any excess payment
  • Health Cash Plan via Medicash
  • Life Assurance (4× earnings at time of death)
  • Enhanced Company Sick Pay
  • A discretionary annual bonus

After 2 Years



  • Increase in Employer Pension to 6% (to a minimum employee contribution of 3%)
  • Enhanced Maternity Pay
  • Enhanced Paternity Pay

After 4 Years



  • Increase in Employer’s Pension to 7% (to a minimum employee contribution of 3.5%)


#J-18808-Ljbffr

Related Jobs

View all jobs

Quantitative Analyst

Quantitative Analyst

Quantitative Analyst

Quantitative Analyst

Quantitative Analyst (Commodities) - Director/Snr Director - London

Quantitative Analyst (Equities & Equity Derivatives - VP)

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.

Neurodiversity in Data Science Careers: Turning Different Thinking into a Superpower

Data science is all about turning messy, real-world information into decisions, products & insights. It sits at the crossroads of maths, coding, business & communication – which means it needs people who see patterns, ask unusual questions & challenge assumptions. That makes data science a natural fit for many neurodivergent people, including those with ADHD, autism & dyslexia. If you’re neurodivergent & thinking about a data science career, you might have heard comments like “you’re too distracted for complex analysis”, “too literal for stakeholder work” or “too disorganised for large projects”. In reality, the same traits that can make traditional environments difficult often line up beautifully with data science work. This guide is written for data science job seekers in the UK. We’ll explore: What neurodiversity means in a data science context How ADHD, autism & dyslexia strengths map to common data science roles Practical workplace adjustments you can request under UK law How to talk about your neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in data science – & how to turn “different thinking” into a real career advantage.

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.