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Data Scientist
Barnsley Football Club
- Bolton, England, United Kingdom
- Bolton, England, United Kingdom
About
Main areas of responsibility
Explore, clean, and prepare datasets for statistical and machine learning modelling.
Develop, validate, and maintain quantitative models using appropriate techniques and libraries.
Perform feature engineering, model selections, and hyperparameter tuning.
Evaluate model performance using suitable metrics and validation strategies.
Monitor models over time to detect performance degradation, drift, or bias.
Recommend and implement model improvements as new data or requirements emerge.
Produce clear documentation, visualisations, and presentations explaining model outputs and implications.
Translate football specific questions into well-defined modelling solutions.
General Responsibilities
BWFC seek to ensure that all children and young people are protected and kept safe from harm while they are with staff and volunteers within Bolton Wanderers activities. Everyone at Bolton Wanderers has a safeguarding responsibility to all work colleagues, fans and any vulnerable adults and children.
Comply fully with all data protection and confidentiality obligations, ensuring that personal, sensitive, and confidential information is handled lawfully, securely, and in accordance with UK GDPR and the Club's Data Protection and Confidentiality Policies.
Be an ambassador of the Group, providing excellent customer service at all times whilst portraying a professional image.
Perform other duties as required, which are considered relevant to the post and to the objectives of the Group as identified by the Lead Recruitment & Data Analyst.
Treat all colleagues as customers ensuring respectful positive outcomes across communications.
Adhere to and abide by all BWFC policies, procedures, and guidelines especially remembering responsibilities to others under Equal Opportunities, Health and Safety, Equality and Diversity.
This post is subject to a DBS disclosure.
About The Candidate Qualifications
Bachelors degree in Computer Science, Physics, Mathematics, Statistics, Engineering, or a related quantitative discipline (or equivalent practical experience)
Experience
Strong experience in Python.
Experience writing SQL to extract, join, and manipulate data from relational databases or data warehouses.
Experience preparing datasets for modelling, including data cleaning, feature engineering, and validation.
Proven experience building and deploying statistical and machine learning models using Python libraries such as SciPy, scikit-learn, TensorFlow (or similar deep learning frameworks)
Strong understanding of: Probability and statistics, supervised and unsupervised learning techniques & model evaluation, validation, and selection.
Experience selecting appropriate modelling approaches based on data characteristics and objectives.
Ability to evaluate, monitor and diagnose model performance over time.
Knowledge, Skills and Qualities
Ability to prepare and present clear documentation, visualisations, and insights for stakeholders.
Comfortable explaining complex modelling concepts and results to non-technical audiences.
Resilience and problem-solving attitude.
Strong organisational and planning skills.
Ability to effectively prioritise work.
Qualifications
Masters degree in Computer Science, Data Science, Statistics, or a related field.
Experience
Experience with web scraping and ingesting data from external sources.
Familiarity with data architecture concepts, including data pipelines and data storage design.
Experience with Snowflake or similar cloud-based data warehouses.
Understanding of applied modelling challenges in sports performance, recruitment, or tactics.
Experience with version control (e.g. Git).
Familiarity with experiment tracking or model management tools (e.g. MLflow, Weights & Biases).
Knowledge, Skills and Qualities
Evidence of previous work, such as: GitHub repositories, Academic or industry research, technical blogs or notebooks, open-source contributions.
About The Club As a founder member of the Football League (EFL), Bolton Wanderers is a football club that is internationally renowned, having played in all four professional leagues of English football, as well as winning the FA Cup on four occasions.
Since the 2019 acquisition by Football Ventures (Whites) Ltd, a new chapter is underway for Bolton Wanderers and Bolton Stadium Hotel, focused on actively shaping a dynamic and enduring future. We are committed to a distinctive approach, driving the club's progress with ambitious plans realised through practical, genuine and comprehensive strategies.
As we continue striving towards achieving greater success, we now have a fantastic opportunity for a Data Scientist to join our Analyst team.
As as equal opportunities employer, Bolton Wanderers Football Club is committedto the equal treatment of all current and prospective employees and does not condone discrimination on the basis of age, disability, sex, sexual orientation, pregnancy and maternity, race or ethnicity, religion or belief, gender identity, or marriage and civil partnership.
We aspire to have a diverse and inclusive workplace and strongly encourage suitably qualified applicants from a wide range of backgrounds to apply and join us.
BWFC seek to ensure that all children and young people are protected and kept safe from harm while they are with staff and volunteers within Bolton Wanderers activities. Everyone at Bolton Wanderers has a safeguarding responsibility to all work colleagues, fans and any vulnerable adults and children.
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Languages
- English
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