Cons Prod Strategic Analyst IV - Fraud Data Science Modeling

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. Responsible Growth is how we run our company and how we deliver for our clients, teammates, communities and shareholders every day.

One of the keys to driving Responsible Growth is being a great place to work for our teammates around the world. We’re devoted to being a diverse and inclusive workplace for everyone. We hire individuals with a broad range of backgrounds and experiences and invest heavily in our teammates and their families by offering competitive benefits to support their physical, emotional, and financial well-being.

Bank of America believes both in the importance of working together and offering flexibility to our employees. We use a multi-faceted approach for flexibility, depending on the various roles in our organization.

Working at Bank of America will give you a great career with opportunities to learn, grow and make an impact, along with the power to make a difference. Join us!

Job Description:
This job is responsible for performing more complex analysis aimed at improving portfolio risk, profitability, performance forecasting, and operational performance for consumer products and related divisions, such as credit cards. Key responsibilities include applying knowledge of multiple business and technical-related topics and independently driving strategic improvements, large-scale projects, and initiatives. Job expectations include working with business counterparts within the Line of Business and partner organizations including Risk and Product teams.

Fraud Prevention and Detection is looking for an energetic and inquisitive senior data scientist to join our team and help us combat financial crime using graph databases. In this role, you will be expected to work on large and complex data science projects. Collaborating with internal strategy, technology, product, and policy partners to deploy advanced analytical solutions with the goal of reducing fraud losses, lowering false positive impacts, improving client experience, and ensuring the Bank minimizes its total cost of fraud.

Responsibilities:

Some tasks that this role may be responsible for include (but are not limited to):

• Performs complex analysis of financial models, market data, financial data, and portfolio trends to understand product performance and improve portfolio risk, profitability, performance forecasting, and operational performance

• Coaches and mentors peers to improve proficiency in a variety of systems and serves as a subject matter expert on multiple business and technical-related topics

• Identifies business trends based on economic and portfolio conditions and communicates findings to senior management

• Supports execution of large scale projects, such as platform conversions or new project integrations by conducting advanced reporting and drawing analytics based insights

• Link Analysis/Graph analytics to find and mitigate densely connected fraud networks

• Developing and tuning graph algorithms to maximize detection of fraud

• Assist with the generation, prioritization, and investigation of fraud rings

Required Qualifications:

• A minimum of 4 years of experience in data and analytics is required

• Must be proficient with SQL and one of SAS, Python ,or Java

• Critical problem-solving skills including selection of data and deployment of solutions

• Proven ability to manage projects, exercise thought leadership and work with limited direction on complex problems to achieve project goals while also leading a broader team

• 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

• Expertise handling data across its lifecycle in a variety of formats and storage technologies (e.g., structured, semi-structured, unstructured; graph; hadoop; kafka)

• Expertise in data analytics and technical development lifecycles including having coached junior staff

Desired Qualifications:

• Advanced Quantitative degree (Masters or PhD)

• 7+ years of experience; work in financial services is very helpful, with preference to fraud, credit, cybersecurity, or other heavily quantitative areas

• Understanding of advanced machine learning methodologies including neural networks, ensemble learning like XGB, and other techniques

• Proficient with H2O or similar advanced analytical tools

Skills:

• Analytical Thinking

• Business Analytics

• Data and Trend Analysis

• Fraud Management

• Problem Solving

• Collaboration

• Innovative Thinking

• Monitoring, Surveillance, and Testing

• Presentation Skills

• Risk Management

• Data Visualization

• Interpret Relevant Laws, Rules, and Regulations

• Issue Management

• Oral Communications

• Written Communications

Shift:

Hours Per Week: