Senior Data Scientist

Job Description

Senior Data Scientist

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Location : 5 day onsite Washington DC, New Jersey, Alpharetta, GA

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Role Summary

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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.

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Key Responsibilities

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Design, build, and optimize Generative AI, LLM, and multimodal foundation models for enterprise fintech applications.

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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.

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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.

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Implement model monitoring, drift detection, and continuous retraining strategies. Evaluate and operationalize new AI technologies, foundation model architectures, responsible AI frameworks, and emerging research.

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Drive POCs and innovation initiatives that enhance AI capabilities and differentiate our products.

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Required Qualifications

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Master s or PhD in Computer Science, Data Science, Machine Learning, AI, or related field.

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8+ years of hands-on experience building and deploying machine learning models in production.

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Proven expertise with LLMs, transformer architectures, transfer learning, and model fine-tuning.

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Strong proficiency in Python, PyTorch or TensorFlow, and ML libraries such as Transformers.

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Experience with cloud ML platforms, containerization (Docker/Kubernetes), and MLOps tools.

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Solid understanding of statistical modeling, optimization, and evaluation methodologies.

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Strong communication skills and ability to collaborate in cross-functional, fast-paced environments.

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Preferred Qualifications

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Experience working in fintech, payments, banking, or fraud/risk environments.

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Background in vector databases, RAG pipelines, and knowledge graph integration.

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Experience with data privacy, model governance, and Responsible AI frameworks.

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Contributions to open-source AI/ML communities or research publications.

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