Data Scientist I - Client Protection - Link

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 is core to how we drive Responsible Growth. This includes our commitment to being an inclusive workplace, attracting and developing exceptional talent, supporting our teammates’ physical, emotional, and financial wellness, recognizing and rewarding performance, and how we make an impact in the communities we serve.

Bank of America is committed to an in-office culture with specific requirements for office-based attendance and which allows for an appropriate level of flexibility for our teammates and businesses based on role-specific considerations.

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.

Client Protection Shared Services – Advanced Analytics is looking for an energetic and inquisitive data scientist to join our team and help us combat financial crime. In this role, you will be expected to work on large and complex data science projects that entail working with both relational and graph databases. In these projects, it is expected to collaborate 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. Key responsibilities include applying knowledge of multiple business and technical-related topics and independently driving strategic initiatives, large-scale projects, and overall improvements.

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

• Performs graph analytics to find and mitigate densely connected fraud networks, leveraging cross-portfolio and graph data

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

• Enables business analytics, including data analysis, trend identification, and pattern recognition, using advanced techniques to drive decision making and data driven insights

• Ensures proper documentation of datasets, analytical methods, and assumptions to maintain reproducibility and transparency

• Manages multiple priorities while ensuring quality and timeliness of work deliverables, including data science products, data analysis reports, and data visualizations, with the ability to work both independently and collaboratively in a team environment

• Manages relationships with multiple technology teams, development team, and line of business partners, ensuring alignment of roadmaps, project execution, and risk management

• Supports execution of large-scale projects, such as model deployments a