Senior Data Scientist

BBI; Washington (District of Columbia); On-site; USD 140,000 - 200,000; Full time

Job summary

BBI is seeking a Senior Data Scientist with deep expertise in ML, AI, LLMs, and foundation models to build enterprise fintech AI applications at the Washington Navy Yard. You will design, fine-tune, and deploy models for risk scoring, document intelligence, anomaly detection, and predictive analytics.

The role requires a MS or PhD, 8+ years of hands-on experience, strong Python and PyTorch/TF, and cloud ML skills.

Qualifications

• MS or PhD in a relevant field
• 8+ years hands-on ML experience
• Strong Python and PyTorch/TensorFlow knowledge
• Experience with LLMs and foundation models
• Cloud ML platforms and MLOps tooling

Responsibilities

• Design, build, and optimize Generative AI, LLMs, and foundation models for fintech applications
• Fine-tune open-source and proprietary models for NLP, document intelligence, risk scoring, and predictive analytics
• Lead experiments to evaluate model accuracy, scalability, and fairness; deploy on cloud pipelines (Azure, AWS)
• Work with large-scale datasets across payments and financial ecosystems; monitor drift; retrain models

Job description

Location : 5 day onsite Washington Navy Yard, District of Columbia.

Role Summary

We are seeking a highly skilled Senior Data Scientist with expertise in Machine Learning, Artificial Intelligence, Large Language Models (LLMs), foundation models, and fine-tuning techniques. This position is ideal for someone who is passionate about building enterprise-grade AI & ML applications and applying cutting-edge techniques to real-world financial and payments challenges.

Key Responsibilities

• Design, build, and optimize Generative AI, LLM, and multimodal foundation models for enterprise fintech applications.
• Fine-tune or adapt open-source and proprietary models Build high-performance models for NLP, document intelligence, anomaly detection, risk scoring, predictive analytics, and decisioning use cases.
• Lead experimentation to evaluate model accuracy, scalability, and fairness. Partner with engineering teams to deploy models on cloud-based ML pipelines (Azure, AWS) & data platforms (Databricks & Snowflake) Work with large-scale structured and unstructured datasets across the payments and financial ecosystem.
• Implement model monitoring, drift detection, and continuous retraining strategies. Evaluate and operationalize new AI technologies, foundation model architectures, responsible AI frameworks, and emerging research.
• Drive POCs and innovation initiatives that enhance AI capabilities and differentiate our products.

Required Qualifications

• Master s or PhD in Computer Science, Data Science, Machine Learning, AI, or related field.
• 8+ years of hands-on experience building and deploying machine learning models in production.
• Proven expertise with LLMs, transformer architectures, transfer learning, and model fine-tuning.
• Strong proficiency in Python, PyTorch or TensorFlow, and ML libraries such as Transformers.
• Experience with cloud ML platforms, containerization (Docker/Kubernetes), and MLOps tools.
• Solid understanding of statistical modeling, optimization, and evaluation methodologies.
• Strong communication skills and ability to collaborate in cross-functional, fast-paced environments.

Preferred Qualifications

• Experience working in fintech, payments, banking, or fraud/risk environments.
• Background in vector databases, RAG pipelines, and knowledge graph integration.
• Experience with data privacy, model governance, and Responsible AI frameworks.
• Contributions to open-source AI/ML communities or research publications.