At a Glance
- Tasks: Analyze cricket data, develop predictive models, and create fan engagement tools.
- Company: CricViz is a leader in cricket data analysis, working with top competitions worldwide.
- Benefits: Enjoy a hybrid work model, pension scheme, life insurance, and flexible employee benefits.
- Why this job: Join a dynamic team to drive data-driven growth in the exciting world of cricket.
- Qualifications: Bachelor’s or Master’s in Data Science or related field; 2+ years experience preferred.
- Other info: Passion for cricket and familiarity with sports analytics is a plus.
The predicted salary is between 36000 - 60000 £ per year.
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.
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.
Responsibilities
Data Analysis & Modeling:
- Analyze complex cricket datasets to extract meaningful insights and support business decisions.
- Develop and implement predictive models using machine learning and statistical techniques.
- Collaborate with the team to enhance existing models and develop new analytical tools.
Product Development:
- Work with the Product team to integrate data science solutions into our product offerings.
- Contribute to the creation of performance analysis tools for clients in Professional Cricket teams and the Broadcast and Media sectors.
- Assist in the development of data-driven features for clients in the Fantasy and Gaming space.
- Adhere to industry best practices in data science, including model development, validation, and documentation.
- Stay updated with the latest advancements in machine learning and AI to incorporate into CricViz’s offerings.
- Participate in code reviews and contribute to maintaining high-quality standards within the data science team.
Requirements
Experience & Education:
- Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Mathematics, or a related field.
- 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:
- Proficiency in Python (especially the PyData stack: pandas, numpy, scikit-learn, XGBoost), and experience with Git for version control is essential.
- 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.
- Experience in building, validating, and deploying predictive models, ensuring they meet business objectives.
- Experience with data visualization tools such as Matplotlib, Tableau, Plotly, Dash.
- Familiarity in leveraging automation and AI tools for coding and writing purposes is a plus.
Analytical & Problem-Solving Skills:
- Ability to work with large, complex datasets and derive actionable insights.
- Proven track record of developing models that simplify data for non-technical audiences.
- Excellent communication and interpersonal skills to effectively collaborate with team members and stakeholders.
- Ability to present complex information clearly and concisely to diverse audiences.
Industry Knowledge:
- A strong understanding and passion for cricket is highly desirable.
- Familiarity with the fantasy and gaming space within sports is a plus.
Equality & Diversity
CricViz is committed to building an open and inclusive culture that supports personal development and learning. CricViz 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.
- Hybrid role with an expectation to work from our new offices in London and Leeds when required.
- Company pension scheme.
- Company life insurance.
- 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.
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Data Scientist employer: Ellipsedata
Contact Detail:
Ellipsedata Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Make sure to showcase your passion for cricket during the interview. Since CricViz is deeply rooted in the sport, demonstrating your knowledge and enthusiasm can set you apart from other candidates.
✨Tip Number 2
Familiarize yourself with CricViz's existing products and services. Understanding how they leverage data in performance analysis and fan engagement will help you discuss how you can contribute to their goals.
✨Tip Number 3
Prepare to discuss specific machine learning projects you've worked on, especially those that involved predictive modeling or data visualization. Be ready to explain your thought process and the impact of your work.
✨Tip Number 4
Network with current employees or alumni who have experience in sports data science. They can provide valuable insights into the company culture and expectations, which can help you tailor your approach.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data science, particularly any work related to sports analytics. Emphasize your proficiency in Python and machine learning techniques that align with the job requirements.
Craft a Compelling Cover Note: In your cover note, clearly outline your relevant experience and how it relates to the responsibilities of the Data Scientist role at CricViz. Mention specific projects or achievements that demonstrate your analytical skills and passion for cricket.
Showcase Technical Skills: Be explicit about your technical skills in your application. List your experience with tools like pandas, numpy, and scikit-learn, and provide examples of predictive models you have developed or worked on.
Demonstrate Industry Knowledge: Express your understanding and passion for cricket in your application. If you have experience in the fantasy and gaming space within sports, make sure to highlight this as it is considered a plus for the role.
How to prepare for a job interview at Ellipsedata
✨Show Your Passion for Cricket
Since CricViz is deeply rooted in cricket data analysis, make sure to express your enthusiasm for the sport. Share any relevant experiences or insights you've gained from following cricket, as this will demonstrate your genuine interest in the company's mission.
✨Highlight Your Technical Skills
Be prepared to discuss your proficiency in Python and the PyData stack. Provide examples of projects where you've utilized machine learning algorithms and data visualization tools. This will showcase your technical expertise and how it aligns with the role's requirements.
✨Prepare for Problem-Solving Questions
Expect to tackle questions that assess your analytical and problem-solving skills. Practice explaining how you would approach analyzing complex datasets and developing predictive models. Use clear examples to illustrate your thought process and decision-making.
✨Communicate Clearly and Concisely
Effective communication is key, especially when presenting complex information. Practice summarizing your past projects and findings in a way that is accessible to non-technical audiences. This will demonstrate your ability to collaborate with diverse stakeholders.