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 Summary:
This job is responsible for reviewing and interpretating large datasets to uncover revenue generation opportunities and ensuring the development of effective risk management strategies. Key responsibilities include working with lines of business to comprehend problems, utilizing sophisticated analytics and deploying advanced techniques to devise solutions, and presenting recommendations based on findings. Job expectations include demonstrating leadership, 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:

Perform graph analytics to find and mitigate densely connected fraud networksAssist with the generation, prioritization, and investigation of fraud ringsEnable business analytics, including data analysis, trend identification, and pattern recognition, using advanced techniques to drive decision making and data driven insightsUnderstanding of end-to-end model development work, ranging from supervised, unsupervised, and graph-based machine learning solutions, to maximize detection of fraud or capture anomalous behaviorManage multiple priorities and ensures quality and timeliness of work deliverables such as data science products, data analysis reports, or data visualizations, while exhibiting the ability to work independently and in a team environmentManage relationships with multiple technology teams, development team, and line of business leaders, including alignment of roadmaps, managing projects, and managing risksOversee development, delivery and quality assurance for data science use cases delivered to the production environment and other areas of the line of businessSupport the identification of potential issues and development of controlsSupport execution of large-scale projects, such as platform conversions or new project integrations by conducting advanced reporting and drawing analytical-based insightsManages a roadmap of data science use cases to answer business trends based on economic and portfolio conditions and communicate findings to senior management, while diligently working and leading peers to solve for these use casesCoach and mentor peers to improve proficiency in a variety of systems and serve as a subject matter expert on multiple business and technical-related topicsApply agile practices for project management, solution development, deployment, and maintenanceDeliver presentations in an engaging and effective manner through in-person and virtual conversations that communicates technical concepts and analysis results to a diverse set of internal stakeholders, and develops professional relationships to foster collaboration on work deliverablesMaintain knowledge of the latest advances in the fields of data science and artificial intelligence to support business analyticsEngage business and technology senior leaders on reporting of project/deliverable statuses, opportunity identification, and planning efforts

Required Qualifications:

4+ years of experience in data and analytics4+ years of experience in data analytics within fraud preventionMust be proficient with SQL and one of SAS, Python, or JavaMust have familiarity with Graph databases (e.g. TigerGraph, Neo4J) and graph query languagesProblem-solving skills including selection of data and deployment of solutionsProven ability to manage projects, exercise thought leadership and work with limited direction on complex problems to achieve project goals while also leading a broader teamExcellent communication and influencing skillsThrives in fast-paced and highly dynamic environmentIntellectual curiosity and strong urge to figure out the “whys” of a problem and produce creative solutionsExposure to model development leveraging supervised and unsupervised machine learning (regression, tree-based algorithms, etc.)Expertise in data analytics and technical development lifecycles including having coached junior staffExpertise handling and manipulating data across its lifecycle in a variety of formats, sizes, and storage technologies to solve a problem (e.g., structured, semi-structured, unstructured; graph; hadoop; kafka)

Desired Qualifications

Advanced Quantitative degree (Master’s or PhD)7+ years of experience; work in financial services is very helpful, with preference to fraud, credit, cybersecurity, or other heavily quantitative areasUnderstanding of advanced machine learning methodologies including neural networks, graph algorithms, ensemble learning like XGB, and other techniquesProficient with SPARK, H2O, or similar advanced analytical toolsAnalytical and Innovating ThinkingProblem Solving and Business AcumenRisk and Issue Management, interpreting relevant laws, rules, and regulationsData Visualization, Oral and Written Communication, and Presentation SkillsExperience managing multi-year roadmaps, engaging technical and non-technical stakeholders, and leading large cross-functional formal projectsExperience influencing mid to senior (executive) level leadersExperience managing risk and issue remediationUnderstanding of computer science topics like automation, code versioning, computational complexity, parallel processing, requirements gathering, testing methodologies, and development lifecycle models like Agile

Skills:

Agile PracticesApplication DevelopmentDevOps PracticesTechnical DocumentationWritten CommunicationsArtificial Intelligence/Machine LearningBusiness AnalyticsData VisualizationPresentation SkillsRisk ManagementAdaptabilityCollaborationConsultingNetworkingPolicies, Procedures, and Guidelines Management

It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil ​liability.​  

Shift:

1st shift (United States of America)

Hours Per Week: 

40