Assistant Data Scientist

Blackburn Rovers

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Blackburn Rovers Senior Training Centre, Blackburn, UK

Salary:

🥅 sports

Data Engineer

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.
5. Qualifications required:	Essential · MSc Data Science, Computer Science or industry equivalent. Desirable · Working towards PhD in relevant area of data science;
DBS check required:	Yes (Enhanced)