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Posted on 2026/10/29
AI Data Scientist
Fiserv
Pacific, WA, United States
Full-time
Overview
In this role you will design and deliver advanced AI/ML and generative AI solutions for high-volume fintech use cases, spanning fraud, risk, forecasting, and payment optimization.
You will own the end-to-end data science lifecycle and partner across product, engineering, and business teams to move research into production.
You’ll build scalable pipelines on cloud/MLOps platforms, ensure data integrity and responsible AI, and mentor peers. This is a hands-on role with a global impact on payments and financial services.
Responsibilities
- Design, develop, and deploy AI/ML solutions for complex business problems in payments and financial services
- Own problem formulation, data exploration, feature engineering, experimentation, and deployment
- Apply AI to merchant/consumer intelligence, fraud/risk, forecasting, anomaly detection, and optimization
- Collaborate with cross-functional teams and mentor data scientists
- Develop scalable AI/ML pipelines with testing, observability, governance, and performance optimization
- Create training/evaluation datasets while ensuring data privacy and responsible AI practices
- Develop domain-specific models via prompt/context engineering, fine-tuning, and model evaluation
- Build generative and agentic AI solutions including foundation-model applications and multi-agent systems
Key requirements
- 5+ years delivering high-impact AI solutions in tech/fintech/financial services
- 2+ years developing LLM/generative AI solutions including autonomous agents and RAG pipelines
- Production-grade AI/ML experience on Azure, AWS, Databricks, Snowflake or similar
- Strong Python and SQL with PyTorch, scikit-learn, XGBoost, Spark experience
- Deep expertise in ML/DL, forecasting, anomaly detection, optimization, model validation
- Fintech/payments domain knowledge and handling high-volume transactional data
- Bachelor's in Computer Science, AI, Data Science or related quantitative field
- Cross-functional collaboration
- Mentoring and leadership
- Communication of complex AI concepts to non-technical stakeholders
- Python
- SQL
- PyTorch
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