Lead Data Scientist

Experience

12–15+ Years (Data Science, Machine Learning & Advanced Analytics Experience)

Full-Time (W2 Only)

USA (Hybrid / Onsite)

We are seeking a highly accomplished Lead Data Scientist to lead the design, development, and deployment of enterprise-scale data science, machine learning, and AI-driven solutions. The ideal candidate will possess deep expertise in Statistical Modeling, Machine Learning, Deep Learning, Predictive Analytics, Large Language Models (LLMs), and Cloud-Based AI Platforms
, with proven leadership experience delivering scalable data science solutions that drive business value.

This role requires ownership of data science strategy, model development, AI innovation, predictive analytics, model deployment, MLOps, and enterprise AI initiatives
.

• Lead enterprise-wide Data Science and Machine Learning initiatives from concept to production.
• Design, develop, and deploy predictive models, machine learning algorithms, and advanced analytics solutions.
• Build scalable AI and Generative AI applications using LLMs, RAG, and intelligent automation frameworks.
• Perform exploratory data analysis (EDA), feature engineering, statistical modeling, and model evaluation.
• Develop end-to-end ML pipelines including data ingestion, preprocessing, training, deployment, and monitoring.
• Collaborate with Data Engineers, AI/ML Engineers, Architects, Product Owners, and business stakeholders.
• Optimize model accuracy, scalability, reliability, and production performance.
• Implement MLOps best practices for model versioning, deployment automation, governance, and monitoring.
• Translate business problems into data-driven AI and analytics solutions.
• Mentor Data Scientists and establish enterprise data science standards and best practices.

• Predictive Analytics
• Statistical Modeling
• Data Mining
• Time Series Forecasting
• Classification
• Regression

• Python
• R
• SQL
• Num Py
• Sci Py
• Scikit-learn

• OpenAI GPT
• Gemini
• Prompt Engineering
• RAG (Retrieval-Augmented Generation)
• Lang Chain
• Tensor Flow
• Py Torch
• Natural Language Processing (NLP)
• Computer Vision
• AWS
• MLflow
• Docker

• Databricks
• Py Spark
• Snowflake
• SQL Server
• Data Warehousing
• Power BI
• Tableau
• Matplotlib
• Seaborn
• Plotly
• Proven experience leading enterprise Data Science and AI teams.
• Strong expertise in designing scalable AI and analytics solutions.
• Experience delivering production-grade machine learning and Generative AI applications.
• Ability to translate complex business requirements into data-driven solutions.
• Strong stakeholder management, executive communication, and leadership skills.
• Experience mentoring teams and driving enterprise AI adoption.

• Experience building enterprise AI platforms and intelligent automation solutions.
• Exposure to Agentic AI, Vector Databases, and RAG architectures.
• Microsoft Azure AI Engineer, AWS Machine Learning, Google Professional ML Engineer, or Databricks certifications.
• Experience in Banking, Healthcare, Insurance, Retail, Manufacturing, or Financial Services domains.
• Strong understanding of Responsible AI, AI Governance, and Explainable AI (XAI).