Data Quality Analyst at Mustard Systems – United Kingdom (Hybrid)

Job Description

Description

Mustard Systems is a team of roughly 65 dedicated to developing market-leading sports models and trading strategies. Applications of our research are widespread across multiple sectors, including betting, insurance, finance and the media, as well as advising coaches and owners of sporting teams. We aim to predict sport as accurately as possible, and we achieve this by combining large, rapidly changing datasets with home-grown software and statistical models.

We enjoy a fast-paced, ever-changing environment, offering fresh challenges which are both rewarding and enjoyable. Our ambitions are high, aiming to create best-in-class systems in a highly competitive field. In the coming year, we will be working on expanding our trading strategies and data feeds.

The accuracy of our predictive models, and ultimately, the success of our business, depends on the quality of the data that powers them. We’re looking for a Data Quality Analyst to help ensure our cricket data is consistently clean, complete, and reliable. Your work will ensure our models are built on solid, trustworthy data, from every run scored to each wicket taken.

As a Data Quality Analyst, you will:

• Support our quant team to improve the quality of data used in modelling
• Clean datasets by identifying and correcting inconsistencies, removing duplicates, and resolving errors
• Mapping data from various sources
• Manual collection to fill data gaps when automation is unavailable
• Monitor and maintain data quality dashboards and reports, proactively investigating anomalies or discrepancies as they arise
• Work alongside developers and data engineers to automate and streamline processes for data collection, cleaning, and mapping, where feasible

Requirements
You have:

• Hands-on experience working with structured datasets using Python (including libraries such as Pandas and NumPy) and writing efficient queries in SQL for data extraction, transformation, and validation
• In-depth knowledge of cricket, including familiarity with different formats (Test, ODI, T20), rules, and competitions
• Exceptional attention to detail, with a demonstrated commitment to ensuring data accuracy, completeness, and consistency
• Strong communication skills, capable of clearly conveying data issues, processes, and insights to both technical and non-technical teams
• A degree in a quantitative subject