SCCS Fraud Detection & Advanced Analytics

Bank of America • Boston, MA

1d • Onsite

About The Position

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! SCCS Fraud Prevention and Detection is looking for an experienced data professional to join our team and help combat financial crime. This role is responsible for designing, developing, and deploying advanced analytical and modeling capabilities to detect, prevent, and mitigate fraud across Specialized Consumer Client Solutions. The position operates as a senior individual contributor, partnering closely with executive leadership, product, technology, GIS and fraud operations to translate complex fraud risks into scalable, data‑driven control solutions. The successful candidate will apply advanced data science techniques to large, complex datasets to identify emerging fraud patterns, strengthen detection strategies, and influence platform‑level risk decisions. This role requires deep technical expertise, strong problem‑structuring skills, and the ability to operate independently in a highly complex, fast‑moving risk environment while maintaining strong risk discipline and model governance. This is a senior individual contributor role reporting directly to an executive leader with a broad enterprise risk remit. The position is designed for a highly technical professional who thrives at the intersection of deep analytics, fraud strategy, and platform‑level risk oversight, and who is motivated by solving the Bank’s most complex fraud challenges at scale. This job is responsible for developing and executing long-term strategies for a broad business area, ensuring integration across lines of business to drive growth and market penetration. Key responsibilities include defining resource needs, leading planning and implementation, managing complex projects, overseeing testing and defect resolution, and partnering with stakeholders to deliver outcomes. Job expectations include influencing decisions, ensuring governance, tracking success measures, mitigating risks, and driving innovation through continuous improvement and change leadership.

Requirements

• Strong proficiency in SQL and at least one analytical or data science language (e.g., Python, SAS).
• 4+ years of experience applying data science, analytics, or advanced modeling in fraud, risk, cyber, or financial services domains.
• Demonstrated exceptional attention to detail, with the ability to identify subtle data inconsistencies, behavioral anomalies, and analytical gaps that materially impact fraud outcomes.
• Strong intellectual curiosity and a consistent habit of asking incisive questions to fully understand the why behind observed patterns, model behavior, and fraud outcomes.
• Proven ability to think logically and structure complex problems, breaking ambiguous fraud risks into clear hypotheses, analytical approaches, and testable conclusions.
• Ability to independently assess what data matters, what signals are meaningful, and what analyses are required—rather than relying on predefined scripts or instructions.
• Disciplined analytical judgment, with the ability to distinguish signal from noise and avoid overfitting conclusions based on incomplete or misleading data.
• Track record of producing high‑quality, defensible analysis that stands up to scrutiny from technical peers, risk partners, and senior leadership.
• Demonstrated experience developing, validating, and monitoring production‑grade models.
• Ability to work independently on complex, ambiguous problems with minimal direction.
• Proven ability to translate analytical insights into business and risk decisions.

Nice To Haves

• Bachelor’s degree in a quantitative field (Computer Science, Data Science, Statistics, Engineering, Mathematics) or equivalent practical experience; candidates with a bachelor’s in a related field (e.g., Economics) and a master’s in Data Science will also be considered.
• Experience with fraud detection use cases such as account takeover, market manipulation, synthetic identity, payments fraud, or digital abuse.
• Familiarity with model risk management frameworks and regulatory expectations (e.g., SR 11‑7).
• Experience working with largescale, distributed data environments.
• Prior exposure to vendor model evaluation, proof‑of‑concept testing, or platform integrations.
• Strong executive presence and comfort influencing senior leaders without direct authority.

Responsibilities

• Enables business analytics, including data analysis, trend identification, and pattern recognition, using advanced techniques to drive decision making and collection data driven insights.
• Manages multiple priorities and ensures 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.
• Design, build, and optimize advanced fraud detection models using statistical and machine learning techniques across digital, payment, and platform‑level fraud use cases.
• Perform deep exploratory data analysis to identify emerging fraud trends, behavioral anomalies, and evolving attacker tactics.
• Develop end‑to‑end analytical solutions, from problem definition through model development, validation, deployment, and ongoing performance monitoring.
• Partner with GIS, technology, and fraud strategy teams to embed models into decisioning platforms, balancing fraud loss reduction with customer experience.
• Apply rigorous governance practices, including documentation, explain ability, performance monitoring.
• Evaluate and test new data sources, vendor capabilities, and advanced techniques (e.g., behavioral biometrics, device intelligence, network analytics).
• Conduct root‑cause analysis on material fraud events and performance deviations, translating findings into actionable control enhancements.
• Communicate complex analytical findings clearly to senior and executive‑level stakeholders, influencing risk posture, investment priorities, and product design.
• Serve as a technical thought leader within Fraud Detection, mentoring peers through influence and expertise rather than formal management responsibility.
• Maintain awareness of industry fraud trends, emerging technologies, and regulatory expectations, proactively adapting analytical approaches.
• Develops and implements long-term strategies for a business area
• Manages complex projects from initiation to delivery ensuring milestones and outcomes are met
• Identify and mitigates risk to safeguard project and business objectives
• Influences decision-making and facilitates alignment across teams
• Drives innovation by championing change and continuous improvement

Benefits

• industry-leading benefits
• access to paid time off
• resources and support to our employees so they can make a genuine impact and contribute to the sustainable growth of our business and the communities we serve
• eligible to participate in the annual discretionary plan

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Number of Employees: 5,001-10,000 employees