{"id":3697777,"url":"https://alion.io/job/barclays-fraud-data-scientist-avp","title":"Fraud Data Scientist AVP","company":{"id":12541,"name":"Barclays","domain":"home.barclays","url":"https://alion.io/company/barclays-uk","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":92,"open_postings":192,"ghost_share":0.026,"stale_share":0.38,"repost_share":0.115,"time_to_fill_p50_days":17,"computed_at":"2026-11-05T05:54:30Z"}},"role":"Data Science","role_family":"Data Science","seniority":"head","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Northampton, United Kingdom"],"countries":["GB"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Databricks","optional":false},{"name":"Machine Learning","optional":false},{"name":"Power BI","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"SAS","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Tableau","optional":false}],"status":"live","first_seen_at":"2026-11-03T18:35:37Z","employer_posted_date":"2026-11-03","last_verified_at":"2026-11-05T23:22:54Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"Job Description\nPurpose of the role\nTo use innovative data analytics and machine learning techniques to extract valuable insights from the bank's data reserves, leveraging these insights to inform strategic decision-making, improve operational efficiency, and drive innovation across the organisation.\nAccountabilities\nIdentification, collection, extraction of data from various sources, including internal and external sources.\nPerforming data cleaning, wrangling, and transformation to ensure its quality and suitability for analysis.\nDevelopment and maintenance of efficient data pipelines for automated data acquisition and processing.\nDesign and conduct of statistical and machine learning models to analyse patterns, trends, and relationships in the data.\nDevelopment and implementation of predictive models to forecast future outcomes and identify potential risks and opportunities.\nCollaborate with business stakeholders to seek out opportunities to add value from data through Data Science.\nAssistant Vice President Expectations\nTo advise and influence decision making, contribute to policy development and take responsibility for operational effectiveness. Collaborate closely with other functions/ business divisions.\nLead a team performing complex tasks, using well developed professional knowledge and skills to deliver on work that impacts the whole business function. Set objectives and coach employees in pursuit of those objectives, appraisal of performance relative to objectives and determination of reward outcomes\nIf the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L - Listen and be authentic, E - Energise and inspire, A - Align across the enterprise, D - Develop others.\nOR for an individual contributor, they will lead collaborative assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialisation to complete assignments. They will identify new directions for assignments and/ or projects, identifying a combination of cross functional methodologies or practices to meet required outcomes.\nConsult on complex issues; providing advice to People Leaders to support the resolution of escalated issues.\nIdentify ways to mitigate risk and developing new policies/procedures in support of the control and governance agenda.\nTake ownership for managing risk and strengthening controls in relation to the work done.\nPerform work that is closely related to that of other areas, which requires understanding of how areas coordinate and contribute to the achievement of the objectives of the organisation sub-function.\nCollaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategy.\nEngage in complex analysis of data from multiple sources of information, internal and external sources such as procedures and practises (in other areas, teams, companies, etc).to solve problems creatively and effectively.\nCommunicate complex information. 'Complex' information could include sensitive information or information that is difficult to communicate because of its content or its audience.\nInfluence or convince stakeholders to achieve outcomes.\nAll colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship - our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset - to Empower, Challenge and Drive - the operating manual for how we behave.\nJoin us at Barclays as a Data Scientist, where you will focus on exploring and analysing a variety of data sources to uncover trends, risks and opportunities. As a Data Scientist, you will transform complex datasets into clear, actionable insights that support decision making, improve business outcomes. These insights will be used within our fraud detection systems to detect and deter fraudsters and in doing so protect our clients. You will ensure analytical findings are translated into meaningful recommendations that drive impact.\nTo be successful as a Data Scientist, you must have the following essential skills:\nStrong analytical and programming skills, with hands-on experience using SQL and Python and/or SAS to manipulate and analyse large, complex datasets.\nProven problem-solving capability, with the ability to identify patterns and insights within data and translate them into practical, actionable business solutions.\nExperience managing analytical problems end-to-end, from initial exploration and solution design through to testing, recommendation and implementation.\nStrong communication and stakeholder management skills, with the ability to explain complex analytical concepts and findings clearly to both technical and senior non-technical audiences.\nA degree in Mathematics, Statistics, Computer Science, Data Science or another quantitative discipline, or equivalent relevant professional experience.\nSome other highly valued skills may include\nExperience in financial services, banking or another regulated environment, Fraud Analytics, scam prevention, financial crime, or cybersecurity.\nKnowledge and practical experience of machine-learning techniques, such as classification, anomaly detection, behavioural analytics including appropriate model performance measurement.\nExperience working with modern analytical platforms and technologies such as Databricks, Spark/PySpark, etc.\nKnowledge of BI tools like Tableau, Power BI, etc.\nYou may be assessed on the key critical skills relevant for success in role, such as risk and controls, change and transformation, business acumen strategic thinking and digital and technology, as well as job-specific technical skills.\nThe successful candidate can either be based in Glasgow or 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