Data Scientist I - Model Governance - Fraud Prevention and Detection

About the role

Job Description:

At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. We do this by driving Responsible Growth and delivering for our clients, teammates, communities and shareholders every day. Being a Great Place to Work and providing a culture of caring is core to how we drive Responsible Growth. We are intentional about fostering an inclusive workplace where every teammate has the opportunity to succeed, build a career and contribute to our shared success. This includes attracting and developing exceptional talent, recognizing and rewarding performance, and supporting our teammates’ physical, emotional, and financial wellness through affordable, competitive and flexible benefits. We value the unique perspectives individuals bring from all backgrounds and career paths - whether shaped by military service, community college education, or a wide range of work and life experiences. These journeys foster resilience, leadership and innovation, strengthening our workforce and positively impact the communities we serve. Bank of America is committed to an in-office culture that supports collaboration, engagement, and career development. Our approach includes clear in-office expectations, while providing an appropriate level of flexibility based on role-specific responsibilities and business needs. At Bank of America, you can build a successful career with opportunities to learn, grow, and make an impact. Join us!

Job Description:

This job is responsible for analyzing and interpreting large datasets to uncover potential revenue generation opportunities and develop effective risk management strategies. Key responsibilities include collaborating with key stakeholders to comprehend business problems, utilizing data gathering and analysis techniques to devise solutions, and presenting recommendations based on the findings. Job expectations include demonstrating flexibility, resilience, accountability, a disciplined approach, and a commitment to fostering responsible growth for the enterprise.

Fraud Prevention and Detection is looking for a model validation professional to join our team and help us combat financial crime.

Responsibilities:

Performs business analytics, which includes data analysis, trend identification, and pattern recognition, using advanced techniques (e.g., machine learning, text mining, statistical analysis, etc.) to support decision-making and drive data-driven insights

Applies agile practices for project management, solution development, deployment, and maintenance

Creates and maintains technical documentation, capturing the business requirements and specifications related to the developed analytical solution and its implementation in production

Manages multiple priorities and maintains quality and timeliness of work deliverables such as quantitative models, data science products, data analysis reports, or data visualizations, while exhibiting the ability to work independently and in a team environment

Delivers engaging presentations and engages in both in-person and virtual conversations that effectively communicate technical concepts and analysis results to a diverse set of internal stakeholders, and develops professional relationships to foster collaboration on work deliverables

Mitigates risk by identifying potential issues and developing controls

Researches the latest advances in the fields of data science and artificial intelligence to support business analytics

Developing advanced technical documentation for internally- and vendor-developed models

Working closely with developers to understand how the model works and provide effective challenge to not only push back on methodology but also ensure results are accurate

Partnering with technology and model users to schedule deployments and planning ahead for future model installations

Working with independent model risk management, legal and compliance teams to ensure models are fully validated and approved for usage

Producing analytics to ensure early model results look consistent with expectations

Conducting regular model monitoring and sharing performance results and analytical insights with model stakeholders and users

Supporting Bank policy and governance requirements for Artificial Intelligence models and ensuring any risks of using advanced techniques are identified and mitigated

Tracking model changes after deployment and ensure appropriate documentation reflects any adjustments, patches or updates

Driving model performance analytics above and beyond Model Risk Management policy requirements, including granular performance monitoring, early trend detection, root cause analysis, and gap analysis

Required Qualifications:

Quantitative degrees (either undergraduate or graduate) or relevant certifications and experience

A minimum of 3 years of experience in model validation or development is required

Experience with model governance, model documentation, model monitoring, and interactions with model risk management functions

Strong analytical skills with the ability to investigate performance trends, identify root causes, and recommend solutions.

Must be proficient with SQL and SAS

Excellent technical writing skills

Critical problem solving abilities including selection of data and deployment of solutions

Excellent communication and influencing skills

Thrives in fast-paced and highly dynamic environment

Intellectual curiosity and strong urge to figure out the “whys” of a problem and come up with creative solutions

Desired Qualifications:

Advanced Quantitative degree (Masters or PhD)

5+ years of experience working in model validation.

Experience in financial services (following SR-26-2 guidance is very desirable)

While SAS and SQL are a MUST, working knowledge of Python is highly desired

Skills:

Adaptability

Attention to Detail

Business Analytics

Technical Documentation

Written Communications

Agile Practices

Application Development

Collaboration

Data Visualization

DevOps Practices

Artificial Intelligence/Machine Learning

Networking

Policies, Procedures, and Guidelines Management

Presentation Skills

Risk Management

Shift:

1st shift (United States of America)

Hours Per Week:

40