Data Scientist

CricViz
London
3 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

CricViz has established itself as the market leader in the collection, analysis and dissemination of data across the world’s leading cricket competitions. CricViz has the largest and most sophisticated database in world cricket. This creates unique opportunities for the company to become the world leader in cricket insight and analysis.

Our work spans several verticals, including Performance Analysis, Broadcast and Media, and Fantasy and Gaming platforms. As CricViz continues to grow, we are looking to scale rapidly to capitalize on our vast potential.

Role Overview:

CricViz is seeking a talented Data Scientist to join our dynamic team. In this role, you will leverage our extensive cricket data to generate valuable insights, develop predictive models, and create fan engagement tools that drive revenue growth across our key verticals. You will collaborate closely with the Data Science and Product teams, and other stakeholders to support the data-driven growth of the business.

Key Responsibilities:

Data Analysis & Modeling:

  1. Analyze complex cricket datasets to extract meaningful insights and support business decisions.
  2. Develop and implement predictive models using machine learning and statistical techniques.
  3. Collaborate with the team to enhance existing models and develop new analytical tools.

Product Development:

  1. Work with the Product team to integrate data science solutions into our product offerings.
  2. Contribute to the creation of performance analysis tools for clients in Professional Cricket teams and the Broadcast and Media sectors.
  3. Assist in the development of data-driven features for clients in the Fantasy and Gaming space.
  4. Adhere to industry best practices in data science, including model development, validation, and documentation.
  5. Stay updated with the latest advancements in machine learning and AI to incorporate into CricViz’s offerings.
  6. Participate in code reviews and contribute to maintaining high-quality standards within the data science team.

Key Requirements:

Experience & Education:

  1. Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Mathematics, or a related field.
  2. 2+ years of professional experience in Data Science or equivalent academic experience demonstrating relevant skills, preferably with some exposure to the sports sector.

Technical Skills:

  1. Proficiency in Python (especially the PyData stack: pandas, numpy, scikit-learn, XGBoost), and experience with Git for version control is essential.
  2. Strong understanding of machine learning algorithms including linear/logistic regression, decision trees, random forests, unsupervised methods, and neural networks. Experience with Bayesian and mixed models is a plus.
  3. Experience in building, validating, and deploying predictive models, ensuring they meet business objectives.
  4. Experience with data visualisation tools such as Matplotlib, Tableau, Plotly, Dash.
  5. Familiarity in leveraging automation and AI tools for coding and writing purposes is a plus.

Analytical & Problem-Solving Skills:

  1. Ability to work with large, complex datasets and derive actionable insights.
  2. Proven track record of developing models that simplify data for non-technical audiences.
  3. Excellent communication and interpersonal skills to effectively collaborate with team members and stakeholders.
  4. Ability to present complex information clearly and concisely to diverse audiences.

Industry Knowledge:

  1. A strong understanding and passion for cricket is highly desirable.
  2. Familiarity with the fantasy and gaming space within sports is a plus.

Equality and Diversity:

CricViz is committed to building an open and inclusive culture that supports personal development and learning. Ellipse believes in the principle of equal opportunity in employment and its employment policies for recruitment, training, development and promotion despite any differences based on individual grounds of race, colour, nationality, religion or belief, sex, sexual orientation, marital status, age, ethnic and national origin, disability or gender reassignment.

Benefits:

  1. Hybrid role with an expectation to work from our new offices in London and Leeds when required.
  2. Company pension scheme.
  3. Company life insurance.
  4. Flexible Employee Benefits.

About Ellipse:

CricViz is part of Ellipse, a leading sports data and analytics company comprising CricViz, FootballViz, Horse Racing, RugbyViz (Oval and Stuart Farmer Media Services), and TennisViz. Working with the world's biggest broadcasters, professional teams, and rights holders, we simplify complex data to engage a broad and diverse audience and tell better stories about the sports we love.

To apply, please send your CV to with the subject Data Scientist. Please also include a cover note outlining your relevant experience.

We can not promise to respond to all applicants due to the volume we receive.

#J-18808-Ljbffr

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.

Contract vs Permanent Data Science Jobs: Which Pays Better in 2025?

Data science sits at the intersection of statistics, machine learning, and domain expertise, driving crucial business decisions in almost every sector. As UK organisations leverage AI for predictive analytics, customer insights, and automation, data scientists have become some of the most in-demand professionals in the tech job market. By 2025, data scientists with expertise in deep learning, natural language processing (NLP), and MLOps are commanding top-tier compensation packages. However, deciding whether to become a day‑rate contractor, a fixed-term contract (FTC) employee, or a permanent member of an organisation can be challenging. Each path offers a unique blend of earning potential, career progression, and work–life balance. This guide will walk you through the UK data science job market in 2025, examine the differences between these three employment models, present sample take‑home pay scenarios, and offer strategic considerations to help you determine the best fit for your career.

Data Science Jobs for Non‑Technical Professionals: Where Do You Fit In?

Beyond Jupyter Notebooks Ask most people what a data‑science career looks like and they’ll picture Python wizards optimising XGBoost hyper‑parameters. The truth? Britain’s data‑driven firms need storytellers, strategists, ethicists and project leaders every bit as much as they need statisticians. The Open Data Institute’s UK Data Skills Gap 2024 places demand for non‑technical data talent at 42 % of all data‑science vacancies—roles focused on turning model outputs into business value and trustworthy decisions. This guide highlights the fastest‑growing non‑coding roles, the transferable skills many professionals already have, and a 90‑day action plan to land a data‑science job—no pandas required.

McKinsey & Company Data‑Science Jobs in 2025: Your Complete UK Guide to Turning Data into Impact

When CEOs need to unlock billion‑pound efficiencies or launch AI‑first products, they often call McKinsey & Company. What many graduates don’t realise is that behind every famous strategy deck sits a global network of data scientists, engineers and AI practitioners—unified under QuantumBlack, AI by McKinsey. From optimising Formula One pit stops to reducing NHS wait times, McKinsey’s analytics teams turn messy data into operational gold. With the launch of the McKinsey AI Studio in late 2024 and sustained demand for GenAI strategy, the firm is growing its UK analytics headcount faster than ever. The McKinsey careers portal lists 350+ open analytics roles worldwide, over 120 in the UK, spanning data science, machine‑learning engineering, data engineering, product management and AI consulting. Whether you love Python notebooks, Airflow DAGs, or white‑boarding an LLM governance roadmap for a FTSE 100 board, this guide details how to land a McKinsey data‑science job in 2025.