Lead Data Scientist

Qualifications

• 6+ years of hands-on machine learning experience with proven model deployment.
• Strong background in consulting or professional services with a client-facing focus.
• Expertise in one primary area of ML: predictive, computer vision, or LLM systems.
• Proficient across ML deployment stack including Python, Docker, and EC2 infrastructure.
• Fluent in Python and SQL; familiar with Git and ML frameworks like PyTorch or Scikit-learn.
• Experience with ML lifecycle tools such as MLflow or Weights & Biases.
• M.S. or Ph.D. in a quantitative field, or equivalent professional experience.

Responsibilities

• Own client engagements from problem scoping to solution delivery.
• Lead project teams and serve as the technical point of contact for clients.
• Design, build, and deploy diverse ML solutions for various projects.
• Manage deployment across cloud platforms like SageMaker and Azure ML.
• Mentor both junior and senior data scientists within the team.
• Evaluate and implement emerging ML tools and techniques effectively.

Benefits

• Company-paid medical, vision, dental, and wellness coverage.
• Provision of home office equipment.
• Flexible vacation and sick leave policies.
• Supportive team environment with collaboration.
• Opportunities for company-sponsored events and branded merchandise.