AVP
Financial Services
AVP-DataScientist(QuantitativeAnalytics)
Neural analysis suggests this role is
optimal for Mid candidates.
“AVP - Data Scientist (Quantitative Analytics) at AVP. Skills: Machine learning, Statistical modeling, Quantitative Analytics, Model development, Model deployment. Design, develop, implement, and support mathematical, statistical, and machine learning models and analytics used in business decision-making. Design analytics and modelling solutions to complex business problems using domain expertise”
Industry & Context.
Design analytics and modelling solutions to complex business problems; Solve problems creatively and effectively; Engage in complex analysis of data from multiple sources of information... to solve problems creatively and effectively
Demonstrate conformance to all Barclays Enterprise Risk Management Policies, particularly Model Risk Policy, Ensure all development activities are undertaken within the defined control environment, Mitigate risk, Strengthening controls in relation to the work done, Take ownership for managing risk
What They're Looking For.
Must Have
Direct experience in designing, developing, and deploying machine learning or statistical models within financial services or similarly regulated industries, Working experience coding in Python, Experience with machine learning and distributed data frameworks (e. g. , scikit-learn, PyTorch, Spark), Risk and controls, Change and transformation, Business acumen, Strategic thinking, Digital and technology, Job-specific technical skills
Nice to Have
Experience with cloud platforms (AWS, Azure, or GCP) or ML-focused cloud-based services (e. g. Databricks) for advanced data analytics and/or machine learning, Practical experience applying DevOps/MLOps fundamentals—version control (Git), unit testing, CI/CD pipelines, modular code design—and experience operationalizing models in collaboration with technology teams, An understanding of model risk management, governance, controls, and documentation within the financial services' regulatory environment, Fraud detection, Credit Risk, Anti-Money Laundering (or similar) in consumer banking
What You'll Do.
and support mathematical
and machine learning models and analytics used in business decision-making
Design analytics and modelling solutions to complex business problems using domain expertise
Develop high performing
comprehensively documented analytics and modelling solutions
Implement analytics and models in accurate
Provide ongoing support for the continued effectiveness of analytics and modelling solutions
Design and deliver machine learning solutions that enhance our ability to detect financial crime
and safeguard our customers
Contribute across the full model lifecycle—from initial concept and data exploration through to supporting deployment
How You'll Work.
Team & Collaboration
Collaboration with technology to specify any dependencies required for analytical solutions; Demonstrate efficacy to business users and independent validation teams; Work with technology to operationalise them; Collaborate closely with other functions/ business divisions; Lead a team performing complex tasks; Lead collaborative assignments and guide team members; Identify the need for the inclusion of other areas of specialisation to complete assignments; Perform work that is closely related to that of other areas; Collaborate with other areas of work, for business aligned support areas; Working in close partnership with business stakeholders and engineers; Operationalizing models in collaboration with technology teams
Communication Scope
Communicate complex information; Influence or convince stakeholders to achieve outcomes
Process & Methodology
Set objectives and coach employees in pursuit of those objectives, Appraisal of performance relative to objectives and determination of reward outcomes, Identify new directions for assignments and/ or projects
Full Job Description
# **Job Description** **Purpose of the role** To design, develop, implement, and support mathematical, statistical, and machine learning models and analytics used in business decision-making **Accountabilities** * Design analytics and modelling solutions to complex business problems using domain expertise. * Collaboration with technology to specify any dependencies required for analytical solutions, such as data, development environments and tools. * Development of high performing, comprehensively documented analytics and modelling solutions, demonstrating their efficacy to business users and independent validation teams. * Implementation of analytics and models in accurate, stable, well-tested software and work with technology to operationalise them. * Provision of ongoing support for the continued effectiveness of analytics and modelling solutions to users. * Demonstrate conformance to all Barclays Enterprise Risk Management Policies, particularly Model Risk Policy. * Ensure all development activities are undertaken within the defined control environment. **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 in
Applying for this AVP - Data Scientist (Quantitative Analytics) 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 AVP?
Real rants from real employees. Read before you apply.