Senior Specialist, Data Scientist

Posted Yesterday
Be an Early Applicant
Pittsburgh, PA, USA
Hybrid
Senior level
Fintech • Financial Services
The Role
Build and deploy machine learning models to detect fraudulent payments across wire, ACH, and instant-payment channels. Responsibilities include exploring payment data, engineering features and pipelines, applying explainable AI, measuring model performance, communicating findings, and partnering with fraud, product, and engineering teams to deliver monitored production solutions.
Summary Generated by Built In

We're seeking a future team member to join our Payments Risk Services team as a Data Scientist / Data Engineer. In this role you'll learn our payments data end-to-end and build machine learning models that detect and prevent fraudulent payments. This role is located in Pittsburgh, PA, and is well-suited to a recent college graduate eager to apply data science to a high-impact, real-world problem.

In this role, you'll make an impact in the following ways:

  • Learn the payments data landscape — Explore, profile, and understand transaction, customer, and channel data across payment rails (wire, ACH, RTP/instant) to build the foundation for detection models.
  • Build fraud-detection ML models — Develop, train, and validate supervised and unsupervised models (classification, anomaly detection, graph/network analysis) that flag fraudulent payments in batch and near-real-time.
  • Develop a fraud typology-driven approach — Understand the major categories of payments fraud — account takeover, authorized push payment (APP)/scams, synthetic identity, business email compromise, money mule/laundering patterns — and map each to detection signals and modeling strategies for how to detect and address them.
  • Engineer features and data pipelines — Design and maintain reliable feature pipelines (behavioral, velocity, device, network, and aggregate features) that feed models, partnering with data engineering to move from prototype to production.
  • Leverage AI to strengthen detection — Identify opportunities to apply modern AI techniques (e.g., deep learning, embeddings, LLMs for unstructured signals, foundation/graph models) to improve fraud coverage and reduce false positives.
  • Build explainable AI (XAI) — Apply model-interpretability methods (SHAP, LIME, counterfactuals, reason codes) so fraud analysts, model risk, and regulators can understand why a payment was flagged.
  • Measure and communicate impact — Track model performance (precision/recall, false-positive rate, fraud dollars prevented), and clearly present findings and recommendations to both technical and business stakeholders.
  • Own projects from inception to delivery — Partner with fraud SMEs, product, and engineering to take detection ideas from hypothesis through deployment and monitoring.
  • Stay current — Follow fraud trends, emerging attack patterns, and advances in ML/AI and responsible-AI practices relevant to the banking industry.
  • Grow across the data science domains — Build depth in model science, feature science, and insight science, strengthening core skills in programming, math & statistics, distributed computing, and communicating complex results.
     

To be successful in this role, we're seeking the following:

  • Bachelor's degree in a STEM field (Computer Science, Data Science, Statistics, Mathematics, Engineering, or related), or equivalent experience.
  • Foundational knowledge of machine learning and statistics, and hands-on coding in Python with libraries such as scikit-learn, pandas, and a deep-learning framework (PyTorch/TensorFlow).
  • Familiarity with SQL and working with large datasets; exposure to distributed/cloud data tools (e.g., Spark, cloud data platforms) is a plus.
  • Curiosity about fraud detection, anomaly detection, or risk analytics — a demonstrated approach to understanding a problem domain and translating it into data-driven solutions.
  • Interest in or exposure to explainable AI (XAI) and responsible/ethical AI practices.
  • Strong problem-solving and communication skills, with the ability to explain technical results to non-technical audiences.
  • Internship, academic project, or coursework experience in ML, data engineering, or the financial services industry is a plus.
About Us

At BNY, our culture allows us to run our company better and enables employees’ growth and success. As a leading global financial services company at the heart of the global financial system, we influence nearly 20% of the world’s investible assets. Every day, our teams harness cutting-edge AI and breakthrough technologies to collaborate with clients, driving transformative solutions that redefine industries and uplift communities worldwide.

Recognized as a top destination for innovators, BNY is where bold ideas meet advanced technology and exceptional talent. Together, we power the future of finance – and this is what #LifeAtBNY is all about. Join us and be part of something extraordinary. About the Team

At BNY, our culture speaks for itself, check out the latest BNY news at BNY Newsroom & BNY LinkedIn

 Here’s a few of our recent awards:

  • America’s Most Innovative Companies, Fortune, 2025
  • World’s Most Admired Companies, Fortune 2025
  • “Most Just Companies”, Just Capital and CNBC, 2025

    Our Benefits and Rewards:

    BNY offers highly competitive compensation, benefits, and wellbeing programs rooted in a strong culture of excellence and our pay-for-performance philosophy. We provide access to flexible global resources and tools for your life’s journey. Focus on your health, foster your personal resilience, and reach your financial goals as a valued member of our team, along with generous paid leaves, including paid volunteer time, that can support you and your family through moments that matter.

    BNY is an Equal Employment Opportunity/Affirmative Action Employer - Underrepresented racial and ethnic groups/Females/Individuals with Disabilities/Protected Veterans.

    BNY assesses market data to ensure a competitive compensation package for our employees. The expected base salary for this position when employment commences can be found in the Job Info section at the bottom of the posting. 

    Base salary offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. Base salary is only part of the total rewards package, which may include eligibility for an annual discretionary incentive award. Subject to the terms and conditions of the applicable plans then in effect, eligible employees may enroll in a 401(k) plan as well as participate in Company-sponsored medical, dental, vision, and basic life insurance plans for the employee and the employee’s eligible dependents. Eligible employees also may receive other benefits (including various paid time off benefits, such as vacation and sick time), dependent on the position offered. Details of participation in these benefit plans will be provided if an employee receives an offer of employment.

    If hired, the employee will be in an “at will” position and the Company reserves the right to modify base salary (as well as any other discretionary payments or compensation programs) at any time, including for reasons related to individual performance, Company or individual department/team performance, and market factors.

    Skills Required

    • Bachelor's degree in a STEM field such as Computer Science, Data Science, Statistics, Mathematics, or Engineering, or equivalent experience.
    • Foundational knowledge of machine learning and statistics.
    • Hands-on Python coding using libraries such as scikit-learn and pandas.
    • Experience with or knowledge of a deep-learning framework such as PyTorch or TensorFlow.
    • Familiarity with SQL and large datasets.
    • Curiosity about fraud detection, anomaly detection, or risk analytics.
    • Interest in or exposure to explainable AI and responsible or ethical AI practices.
    • Strong problem-solving and communication skills, including explaining technical results to non-technical audiences.
    • Exposure to distributed or cloud data tools such as Spark or cloud data platforms.
    • Internship, academic project, or coursework experience in machine learning, data engineering, or financial services.

    BNY Compensation & Benefits Highlights

    The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about BNY and has not been reviewed or approved by BNY.

    • Healthcare Strength — Health coverage includes comprehensive options with a $0‑premium plan for eligible lower earners, expanded mental‑health support with personalized therapy, and strong income protection through short‑ and long‑term disability. These features have been recently enhanced and are paired with dental and vision coverage.
    • Parental & Family Support — Parental leave provides 16 weeks of fully paid time for all parents, with added support such as adoption assistance. This breadth offers strong coverage for major family events.
    • Retirement Support — The 401(k) program includes a company match and Roth options to support long‑term savings. Additional financial programs like tuition assistance and savings vehicles complement retirement readiness.

    BNY Insights

    Am I A Good Fit?
    beta
    Get Personalized Job Insights.
    Our AI-powered fit analysis compares your resume with a job listing so you know if your skills & experience align.

    The Company
    HQ: New York, NY
    41,739 Employees

    What We Do

    We help make money work for the world — managing it, moving it and keeping it safe. As a leading global financial services company at the center of the world’s financial system, we touch nearly 20% of the world’s investable assets. Today we help over 90% of Fortune 100 companies and nearly all the top 100 banks globally access the money they need. For 240 years we have partnered alongside our clients to create solutions that benefit businesses, communities and people everywhere.

    Similar Jobs

    BNY Logo BNY

    Data Scientist

    Fintech • Financial Services
    In-Office
    3 Locations
    41739 Employees
    In-Office
    3 Locations
    20252 Employees

    Wipfli Logo Wipfli

    Senior Specialist, Healthcare Revenue Cycle

    Cloud • Fintech • Software • Business Intelligence • Consulting • Financial Services
    Remote or Hybrid
    United States
    2900 Employees
    25K-34K Hourly

    Atlassian Logo Atlassian

    Solution Sales Center of Excellence, Teamwork Collection

    Cloud • Information Technology • Productivity • Security • Software • App development • Automation
    In-Office or Remote
    17 Locations
    11000 Employees

    Similar Companies Hiring

    Hanover Park Thumbnail
    Artificial Intelligence • Fintech • Software • Financial Services
    New York, New York
    42 Employees
    Kepler  Thumbnail
    Artificial Intelligence • Fintech • Software
    New York, New York
    9 Employees
    Onshore Thumbnail
    Artificial Intelligence • Fintech • Software • Financial Services
    New York, New York
    60 Employees

    Sign up now Access later

    Create Free Account

    Please log in or sign up to report this job.

    Create Free Account