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About OneSix
OneSix is a data and AI services firm. We exist to make data and AI work for the businesses where it matters most. We take on the work companies can't afford to get wrong, embedding teams sized to the problem and working inside our clients' operations as partners, not extra hands. We build durable systems that outlast the engagement, and we leave every client more capable and more profitable than we found them.
We work with Healthcare and Life Sciences, Higher Education, Manufacturing, Private Equity, and marketing organizations. We're a Snowflake Elite services partner.
Five values guide our work: Always Truthful, Own the Outcome, Believe in the Work, Team Over Ego, and Learn Here, Lead Here.
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
- 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
- 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.
OneSix provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, familial status, or any other characteristic protected by federal, state, or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.
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