Lead Data Scientist

Job Summary

We are seeking a highly experienced Lead Data Scientist to lead the design, development, and deployment of advanced machine learning and artificial intelligence solutions that drive strategic business decisions. The ideal candidate will have a strong background in statistical modeling, predictive analytics, deep learning, and cloud-based data platforms. As a technical leader, you will collaborate with cross-functional teams, mentor data scientists, and help shape the organization’s data science strategy.

Key Responsibilities

• Lead a team of Data Scientists and Machine Learning Engineers to deliver high-impact AI and analytics projects.
• Design, develop, and deploy scalable machine learning and deep learning models.
• Analyze large structured and unstructured datasets to identify actionable insights.
• Build predictive models for forecasting, customer segmentation, recommendation systems, and risk analysis.
• Collaborate with Product Managers, Software Engineers, Data Engineers, and business stakeholders to translate business needs into AI-driven solutions.
• Develop and optimize feature engineering pipelines and model evaluation frameworks.
• Establish best practices for data science, experimentation, model governance, and MLOps.
• Oversee the deployment, monitoring, and continuous improvement of production ML models.
• Present technical findings and strategic recommendations to executive leadership.
• Mentor junior and senior data scientists through code reviews, technical guidance, and career development.
• Stay current with emerging AI technologies, research, and industry trends to drive innovation.

Required Qualifications

• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, Artificial Intelligence, or a related field (Ph.D. preferred).
• 7–10+ years of professional experience in Data Science, Machine Learning, or Artificial Intelligence.
• Proven experience leading technical teams and managing end-to-end AI projects.
• Strong understanding of statistical analysis, predictive modeling, and machine learning algorithms.
• Experience deploying machine learning models into production environments.
• Excellent problem-solving, communication, and leadership skills.

Required Technical Skills

• Python
• SQL
• R (preferred)
• Machine Learning
• Deep Learning
• Statistics
• Feature Engineering
• TensorFlow
• PyTorch
• Scikit-learn
• Apache Spark
• Hadoop
• Databricks
• MLflow
• Docker
• Kubernetes
• Git
• REST APIs
• AWS (SageMaker, S3, EC2)
• Microsoft Azure Machine Learning
• Google Cloud Platform (Vertex AI)
• Tableau or Power BI

Preferred Qualifications

• Experience with Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Prompt Engineering.
• Knowledge of NLP, Computer Vision, or Time Series Forecasting.
• Experience with vector databases such as Pinecone, Weaviate, or FAISS.
• Familiarity with data governance, responsible AI, and model explainability.
• Experience in Agile or Scrum development environments.

Benefits

• Competitive salary with annual performance bonuses.
• Comprehensive medical, dental, and vision insurance.
• Flexible work arrangements (Remote/Hybrid).
• Paid vacation, holidays, and parental leave.
• Professional development and certification reimbursement.
• Employee wellness programs.
• Career advancement opportunities.