Fraud Analytics
FraudAnalytics-DataScientist
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Fraud Analytics - Data Scientist at Fraud Analytics. Skills: Data Analytics, Machine Learning, Data Science. Identification, collection, extraction of data from various sources. Performing data cleaning, wrangling, and transformation”
What You'll Achieve.
inform strategic decision-making; improve operational efficiency; drive innovation across the organisation; protect our clients; ensuring the ongoing delivery of our analytics optimisation services
Industry & Context.
Engage in complex analysis of data from multiple sources of information... to solve problems creatively and effectively
What They're Looking For.
Must Have
Proficiency in SAS, Python, or similar programming languages, knowledge of fraud detection systems, Hands-on experience working with large and complex data sets
Nice to Have
A background in statistics or mathematics, with fraud experience, Familiarity with BB Plc businesses
What You'll Do.
extraction of data from various sources
Performing data cleaning
Development and maintenance of efficient data pipelines
Design and conduct of statistical and machine learning models
Development and implementation of predictive models
Collaborate with business stakeholders to seek out opportunities to add value from data through Data Science
How You'll Work.
Team & Collaboration
Collaborate with business stakeholders; Collaborate closely with other functions/ business divisions; Lead a team performing complex tasks; Lead collaborative assignments and guide team members; Consult on complex providing advice to People Leaders; Perform work that is closely related to that of other areas; Collaborate with other areas of work
Communication Scope
Communicate complex information; Influence or convince stakeholders
Full Job Description
# **Job Description** **Purpose of the role** To 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. **Accountabilities** * Identification, collection, extraction of data from various sources, including internal and external sources. * Performing data cleaning, wrangling, and transformation to ensure its quality and suitability for analysis. * Development and maintenance of efficient data pipelines for automated data acquisition and processing. * Design and conduct of statistical and machine learning models to analyse patterns, trends, and relationships in the data. * Development and implementation of predictive models to forecast future outcomes and identify potential risks and opportunities. * Collaborate with business stakeholders to seek out opportunities to add value from data through Data Science. **Assistant Vice President Expectations** * To advise and influence decision making, contribute to policy development and take responsibility for operational effectiveness. Collaborate closely with other functions/ business divisions. * Lead 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 * If 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. * OR for an individual contributor, they will lead collaborati
Applying for this Fraud Analytics - Data Scientist role?
Most applicants get filtered before a human reads their resume. See if yours makes the cut.
How to Apply on Workday
- Workday has a multi-step form — save your progress after every section.
- "Apply With LinkedIn" can fail or lose data; manual entry is more reliable.
- Watch for the "Submit for Review" final step — hitting "Save" alone does not submit.
- Job requisition numbers are useful when following up with HR by email.
ANONYMOUS · UNFILTERED
What do employees actually say about Fraud Analytics?
Real rants from real employees. Read before you apply.