At a Glance
- Tasks: Transform complex cricket data into innovative analytical products and predictive models.
- Company: Join CricViz, a leader in cricket data analysis and insights.
- Benefits: Enjoy 25 days holiday, competitive salary, and a commitment to personal development.
- Other info: Be part of an inclusive culture that values diversity and personal growth.
- Why this job: Make an impact in the sports industry with cutting-edge data science techniques.
- Qualifications: 3+ years in data science with expertise in predictive modelling and sports datasets.
The predicted salary is between 60000 - 80000 £ per year.
CricViz has established itself as a market leader in the collection, analysis and dissemination of data across the world’s leading cricket competitions, with the largest and most sophisticated database in world cricket. Our work spans several verticals, including Performance Analysis, Broadcast and Media, and Fantasy and Gaming platforms. We are seeking a highly skilled Data Scientist to join the CricViz team. This pivotal role focuses on the end-to-end development of proprietary metrics and predictive models derived from the world’s most sophisticated cricket databases. You will lead the transformation of complex, high-frequency tracking data into market-leading, commercial-grade analytical products. Your work will empower sophisticated professional clients by surfacing match state insights and player performance indicators not captured by conventional analysis.
The ideal candidate is an experienced Data Scientist/Quantitative Analyst with strong problem-solving skills, capable of working professionally within an evolving and fast-paced environment.
- Metric Innovation: Research and develop new, high-value derived metrics from raw ball and player tracking data, such as pitch behavioural characteristics and advanced fielding analysis.
- Bespoke Client Collaboration: Act as the lead technical point of contact for private clients, working to develop custom predictive models and niche datasets tailored to their specific analytical requirements.
- Productisation of Data: Translate raw tracking data into productionised Data Science models that provide a clear commercial advantage.
- Model Assurance & Validation: Oversee rigorous back testing and optimisation cycles to ensure all models maintain the high level of accuracy and reliability required for professional-grade execution.
- Experience: A minimum of 3 years experience in data science, with a proven track record of handling large-scale, high-granularity sports datasets and feeds.
- Predictive Modeling: Deep proficiency with the PyData stack (pandas, numpy, scikit-learn, XGBoost) and advanced machine learning methods including neural networks and random forests.
- Tracking Data Experience: Prior experience working with high-frequency tracking or GPS data to create aggregated, value-add insights.
- Communication: Ability to translate highly technical modeling concepts into clear commercial value propositions for sophisticated stakeholders.
- Commercial Environment: Experience working in sensitive commercial environments where protecting proprietary modeling work is paramount.
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.
25 days holiday (plus)
Data Marketing Scientist employer: CricViz
CricViz is an exceptional employer, offering a dynamic work environment in the heart of London where innovation meets passion for cricket. With a strong commitment to equality and diversity, employees benefit from 25 days of holiday, opportunities for personal development, and the chance to work with cutting-edge data science techniques in a collaborative culture that values creativity and professional growth.
StudySmarter Expert Advice🤫
We think this is how you could land Data Marketing Scientist
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like CricViz!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Marketing Scientist at CricViz.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like CricViz.
✨Apply Directly through Our Website
When you find a suitable opening like Data Marketing Scientist at CricViz, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Data Marketing Scientist
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at CricViz, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at CricViz. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at CricViz
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at CricViz!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
