Sr. Data Scientist

Job Title: Senior Data Scientist – AI/ML (Banking Domain)
Location: REMOTE  USC / GC Only
Job Type: Contract
EXP: 14+ Years

Job Summary

We are seeking an experienced Senior Data Scientist – AI/ML to support a leading banking client in Buffalo, NY. The ideal candidate will leverage advanced analytics, machine learning, and AI technologies to develop intelligent solutions that enhance risk management, fraud detection, customer insights, regulatory compliance, and operational efficiency. This role requires close collaboration with business stakeholders, data engineers, and technology teams to deliver scalable AI-driven solutions in a highly regulated financial environment.

Key Responsibilities

• Design, develop, and deploy machine learning and AI models to solve complex business problems within the banking and financial services domain.

• Build predictive models for fraud detection, credit risk, customer segmentation, customer churn, anti-money laundering (AML), transaction monitoring, and financial forecasting.

• Analyze large volumes of structured and unstructured banking data to identify trends, anomalies, and actionable insights.

• Develop and optimize feature engineering, model training, validation, and performance tuning processes.

• Build and implement Generative AI and Large Language Model (LLM) solutions to improve knowledge management, customer support, document processing, and operational efficiency.

• Design and implement Retrieval-Augmented Generation (RAG) architectures using vector databases.

• Collaborate with business leaders, compliance teams, risk management, and technology teams to translate business requirements into AI/ML solutions.

• Ensure AI models comply with banking regulations, data governance, privacy, and security standards.

• Deploy machine learning models using MLOps best practices and monitor model performance in production.

• Present analytical findings and recommendations to senior business and technology leadership.

• Stay current with emerging AI technologies, financial industry trends, and regulatory requirements.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field.

• 8+ years of experience in Data Science, Machine Learning, or Artificial Intelligence.

• Hands-on experience in the Banking, Financial Services, or Financial Technology (FinTech) industry.

• Strong expertise in Python and SQL.

• Experience with machine learning frameworks such as Scikit-learn, TensorFlow, PyTorch, or XGBoost.

• Strong knowledge of statistics, predictive modeling, classification, regression, clustering, and optimization techniques.

• Experience working with large enterprise data platforms and cloud environments (AWS, Azure, or GCP).

• Experience building production-grade AI/ML solutions.

• Strong understanding of model governance, explainable AI, and responsible AI practices.

• Excellent communication and stakeholder management skills.

Preferred Qualifications

• Experience developing AI solutions for:

  • Fraud Detection

  • Credit Risk Modeling

  • Anti-Money Laundering (AML)

  • Know Your Customer (KYC)

  • Customer Analytics

  • Transaction Monitoring

  • Financial Forecasting

  • Regulatory Reporting

• Experience with Generative AI, LLMs (OpenAI, Anthropic, Llama, Gemini), RAG, LangChain, LangGraph, or LlamaIndex.

• Experience with vector databases such as Pinecone, Milvus, Weaviate, or ChromaDB.

• Experience with Databricks, Apache Spark, MLflow, Docker, Kubernetes, and CI/CD pipelines.

• Familiarity with banking regulations and governance frameworks.

Required Technical Skills

• Python

• SQL

• Machine Learning

• Deep Learning

• Statistics

• Predictive Analytics

• NLP

• TensorFlow / PyTorch / Scikit-learn

• XGBoost

• Generative AI

• Large Language Models (LLMs)

• RAG

• LangChain

• LangGraph

• MLflow

• Databricks

• Apache Spark

• Docker

• Kubernetes

• AWS / Azure / GCP

• Git

Preferred Banking Experience

Candidates with experience supporting large financial institutions, commercial banks, investment banks, credit card organizations, or digital banking platforms are highly preferred. Experience with risk analytics, fraud prevention, customer intelligence, regulatory compliance, and financial data analytics will be considered a strong advantage.

Thanks & Best Regards,

Prasad

AB Tech Solutions

[email protected]