Lead Data Scientist

OneSix - External

$160K — $200K *
US-Anywhere
+ 2 other locationsRemote
Business Services
5 - 7 years of experience
Job Overview by Ladders

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.
Full Job Description
Lead Data Scientist

OneSix is looking for a Lead Data Scientist to drive ML solutions for clients ranging from scrappy startups to Fortune 500s. This is a true player-coach role - you'll make serious technical contributions and lead a team, mentor junior scientists, and own the client relationship from scoping through delivery.
What You'll Do
  • Own client engagements end-to-end: scope the problem, build the solution, manage expectations, and deliver
  • Lead small project teams and serve as the technical and strategic point of contact for clients
  • Design, build, and deploy ML solutions across a range of domains and use cases in a landscape where no two projects are the same
  • Work across the full deployment spectrum including managed cloud ML platforms (SageMaker, Vertex AI, Azure ML) and containerized Python solutions running on raw infrastructure
  • Mentor junior and senior data scientists and help shape how we practice ML at OneSix
  • Evaluate emerging tools and techniques and bring the right ones to bear on client problems
What You Bring
  • 6+ years of hands-on ML experience with a track record of shipping models to production
  • Background in consulting, professional services, or client-facing delivery strongly preferred, you know how to manage scope, communicate risk, and keep a client confident
  • You have a strong suit in at least one area: predictive/classical ML, computer vision, or LLM/agentic systems. You're comfortable being stretched into adjacent ones
  • Comfortable across the full deployment stack: managed cloud services and building from scratch with Python, Docker, and EC2-style infrastructure. You write clean production code, not just notebook code.
  • Fluency in Python and SQL; comfortable with Git and frameworks like PyTorch, Scikit-learn, or Hugging Face depending on your domain
  • Experience with experiment tracking and ML lifecycle management (MLflow, Weights & Biases, or similar)
  • M.S. or Ph.D. in a quantitative field, or equivalent depth demonstrated through shipped work
  • Strong communicator who can make a complex model legible to a non-technical executive and to a skeptical engineer
  • Must be based in the US or Canada
Compensation / Benefits
  • Competitive compensation
  • Company-paid medical, vision, dental, and wellness benefits for employees
  • Company-provided home office equipment
  • Flexible vacation and sick days
  • Team-oriented and supportive working environment
  • Company-sponsored events and swag

This position offers a base salary in the range of $160,000-$200,000 USD annually, depending on experience and location. Compensation may vary based on factors including geographic location, level of experience, skills, and performance. This salary range reflects base pay only and does not include any additional compensation such as bonuses, equity, or benefits.

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