Job Title: Senior Data Scientist
Location: Washington, DC (Only Local Candidates)
Experience: 12+ Years (Mandatory)
Mandatory Technical Skills:
GenAI / LLMs / NLP: 6+ Years
Python: 6+ Years
PySpark: 6+ Years
PyTorch: 6+ Years
Google Cloud Platform: 3+ Years
Web Development: 3+ Years
Docker: 4+ Years
Kubeflow: 4+ Years
LangChain: Hands-on experience required
Role Summary:
We are seeking a highly skilled Senior Data Scientist with deep expertise in Machine Learning, Artificial Intelligence, Large Language Models (LLMs), foundation models, and fine-tuning techniques.
In this role, you will architect, build, and deploy advanced AI/ML solutions that power Fiserv’s next-generation products across payments, fraud detection, risk decisioning, and financial data enrichment.
This position is ideal for professionals passionate about building enterprise-grade AI/ML applications and applying cutting-edge techniques to real-world fintech challenges.
Key Responsibilities:
Design, build, and optimize Generative AI, LLMs, and multimodal foundation models for enterprise fintech use cases.
Fine-tune and adapt open-source and proprietary AI models.
Develop high-performance models for:
Natural Language Processing (NLP)
Document Intelligence
Anomaly Detection
Risk Scoring
Predictive Analytics & Decisioning
Lead experimentation to evaluate model accuracy, scalability, robustness, and fairness.
Collaborate with engineering teams to deploy models using cloud-based ML pipelines (Azure, AWS) and data platforms (Databricks, Snowflake).
Work with large-scale structured and unstructured datasets across the payments ecosystem.
Implement model monitoring, drift detection, and continuous retraining strategies.
Evaluate and operationalize emerging AI technologies, foundation model architectures, and Responsible AI frameworks.
Drive POCs and innovation initiatives to enhance Fiserv’s AI capabilities.
Required Qualifications:
Master’s or PhD in Computer Science, Data Science, Machine Learning, AI, or a related field.
5+ years of hands-on experience building and deploying ML models in production.
Strong expertise in LLMs, transformer architectures, transfer learning, and fine-tuning.
Proficiency in Python, PyTorch or TensorFlow, and ML libraries such as Transformers.
Experience with cloud ML platforms, Docker/Kubernetes, and MLOps tools.
Solid understanding of statistical modeling, optimization, and evaluation techniques.
Strong communication and cross-functional collaboration skills.
Preferred Qualifications:
Experience in fintech, payments, banking, fraud, or risk domains.
Hands-on experience with vector databases, RAG pipelines, and knowledge graphs.
Knowledge of data privacy, model governance, and Responsible AI practices.
Contributions to open-source AI/ML projects or research publications.
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