Staff Data & Decision Scientist

Fiserv•Berkeley Heights, NJ

6d•Onsite

About The Position

You will design, implement, and deploy prescriptive analytics and optimization models that drive automated, high-impact business decisions. This role goes beyond predictive modeling. You will formulate and solve optimization problems—explicitly defining objectives, constraints, and trade-offs—to support decisions across risk management, limits, and pricing. Yu will sit at the intersection of Operations Research, Decision Science, and Applied Analytics, and partners closely with product, risk, and engineering teams to operationalize optimization in production systems.

Requirements

Bachelor’s / Master’s degree in a quantitative field (Mathematics, Statistics, Computer Science, Operations Research).
Demonstrate hands-on Operations Research or optimization experience.
5 years of relevant risk analytics experience as well as 3 years of experience in driving technical project delivery.
Strong foundation in Operations Research, Applied Mathematics, Industrial Engineering, or Decision Science.
Proven experience formulating and solving optimization problems.
Hands-on experience with one or more of Linear / Integer Programming and Constrained Optimization.
Experience using optimization solvers or OR libraries, such as: Pyomo, Gurobi, PuLP.
Strong Python and SQL skills for data preparation and model integration.

Nice To Haves

Experience applying optimization in financial services, risk management, pricing, limits, or capacity planning.
Experience combining predictive ML models with prescriptive optimization.
Exposure to decision automation or real-time decisioning systems.
Experience deploying optimization models into production workflows.
Agile methodology experience (JIRA, Confluence).
Familiarity with ML model pipelines or feature stores.
Knowledge of credit bureaus and other external data sources.

Responsibilities

Formulate decision problems as mathematical optimization models, explicitly defining decision variables, objective functions, constraints and trade-offs.
Design and implement prescriptive analytics solutions, including linear and integer programming constrained optimization, stochastic or scenario-based optimization (where applicable).
Build optimization models to support business decisions such as credit limits and exposure allocation, fraud and risk prioritization under capacity constraints, pricing, policy thresholds, and approval strategies.
Translate optimization outputs into automated decisioning frameworks deployed in production systems.
Develop predictive models using large datasets. Leverage machine learning as well as traditional techniques in developing best-in-class models as appropriate.
Partner with stakeholders to ensure optimization models reflect real-world operational constraints and business objectives.
Evaluate and communicate trade-offs (e.g., loss vs growth, risk vs approval, cost vs service levels) using decision-centric metrics.
Integrate optimization models with predictive ML outputs (e.g., risk scores feeding prescriptive decisions).
Maintain model governance, documentation, and validation artifacts to support internal and regulatory requirements.
Contribute to continuous improvement of decision frameworks, including sensitivity analysis and scenario testing.

Benefits

Fuel Your Life program to support physical, financial, social, and emotional well-being.
Paid holidays and generous time away policies.
No-cost mental health support through Employee Assistance Programs.
Living Proof program to recognize your peers’ extra effort with points used for rewards.
Eight Employee Resource Groups to foster a collaborative culture.
Unparalleled professional growth with training, development, and internal mobility opportunities.
Retirement planning and discounted shares with the Employee Stock Purchase Plan.
Medical, dental, vision, life, and disability insurance options available day one
Tuition assistance and reimbursement program.
Paid parental, caregiver, and military leave.