Assistant Data Scientist

Job title:

Assistant Data Scientist

Department:

Data Science

Based at:

Blackburn Rovers Senior Training Centre, Brockhall Village, Old Langho, Blackburn, BB6 8FA. Flexibility regrading location is required. 

Reports to:

Head of Data Science and Football Insights

Responsible for:

N/A

Hours of work:

A minimum of 40 hours per week plus any additional hours necessary. This will include regular evening and weekend work.

Contractual Status:

Permanent

1. Job purpose:

To oversee the end-to-end process of gathering, analysing, and translating performance data into strategic insights that support coaches, analysts, and senior leadership in enhancing team and player performance.

2. Duties and responsibilities:

• To be committed to ensuring the safeguarding and welfare of all elite players, promoting their well-being needs whilst maintaining professional boundaries;
• Support the Head of Data Science in managing and optimizing the club’s data infrastructure across performance analysis, scouting and recruitment.
• Centralize and maintain data pipelines from multiple providers (e.g., IMPECT, SkillCorner, Second Spectrum), ensuring accuracy, security, and scalability.
• Automate data collection, cleaning, and storage processes using Python, Power Automate, and other relevant tools.
• Use web-scraping frameworks to gather supplementary datasets where appropriate.
• Apply advanced data science methods to derive new metrics, uncover performance patterns, and inform tactical and strategic decision-making from both event and tracking datasets.
• Produce detailed pre-match opposition analysis and post-match performance reports for the coaching staff.
• Continuously integrate new datasets into the club’s data ecosystem to enhance analytical capabilities.
• Design and maintain clear, insightful, and visually compelling dashboards and reports in Tableau, following best-practice visual analytics principles.
• Work closely with coaches, performance analysts, and medical and sports science teams to translate data into actionable insights that support player performance, welfare, and recruitment.
• Ensure effective communication of complex findings to non-technical stakeholders and promote data literacy across departments.
• Contribute to the alignment of scouting and recruitment workflows by linking scouting data with quantitative models and player profiles from academy to first team.
• Contribute to departmental CPD by staying up to date with emerging methods in football data science and analytics.
• Assist in the publication of up to two peer-reviewed research papers per season in relevant areas of football performance analytics.
• Uphold the club’s safeguarding standards by ensuring that all data processes protect and enhance the physical and mental welfare of players.
• Undertake any additional duties reasonably assigned to support the success and productivity of the Data Science department.

3. Skills required:

• Strong proficiency in Python, SQL, and Tableau for data analysis, visualization, and model development.
• Experience in ETL processes for automated data ingestion, cleaning, and transformation.
• Skilled in data storage, modelling, and management of large relational databases.
• Proficient in cloud-based environments (e.g., AWS, Azure) with experience building scalable and automated data pipelines.
• Familiarity with football event and tracking data (e.g., IMPECT, SkillCorner, Second Spectrum) and version control systems such as Git.
• Working knowledge of data visualization libraries (e.g., Matplotlib, Seaborn) and API integration.
• Excellent understanding of football dynamics, with the ability to interpret and connect data insights to tactical and technical aspects of the game.
• Proven ability to research, analyze, and present complex data through detailed reports and high-quality visual presentations.
• Strong foundation in data science, statistics, computer science, or a related quantitative discipline.
• Excellent written and verbal communication skills, with the ability to convey technical concepts clearly to non-technical stakeholders.
• High attention to detail and strong problem-solving skills.
• Able to work both independently and collaboratively within a multidisciplinary team.
• Strong time-management skills, with the ability to meet tight deadlines and adapt to unexpected situations.
• Flexible and committed to working in line with the needs and schedule of professional football.
• Maintains discretion, professionalism, and high standards of data confidentiality.
• Demonstrates calmness, composure, and sound judgment under pressure.
• Energetic, proactive, and enthusiastic attitude towards learning and contributing to team objectives.

4. Knowledge required:

• Significant experience in data processing, analytics, and model development, ideally within elite or professional sport.
• Proven ability to work with both structured and unstructured datasets, integrating multiple data sources effectively.
• Demonstrated experience applying data-driven insights within high-performance or elite sporting environments to support tactical, technical, and strategic decisions.
• Strong knowledge of football data systems, including event, tracking, and physical datasets, as well as familiarity with established data providers and formats.
• Proficiency in using APIs and data integration tools to manage and automate dataset collection and updates.
• Solid understanding of statistical analysis, performance modelling, and applied data science techniques to enhance football outcomes.
• Awareness of the relationship between football performance, data analytics, and decision-making, and how quantitative insights translate into on-pitch impact.
• Experience conducting research, writing analytical reports, and presenting findings clearly to technical and non-technical audiences.
• Working knowledge of sport science and performance analysis principles, and how these intersect with football data and applied research.
• A genuine passion for football and deep understanding of the game at an elite level.