Lead Data Scientist, Predictive Modeling & Causal Inference

OneSix; Canada (KY); On-site; USD 180,000 - 210,000; Full time

Benefits offered by this job

Medical benefits

Vision benefits

Dental benefits

Wellness program

Home office equipment

Flexible time off

Team-oriented environment

Job summary

OneSix is seeking a Lead Data Scientist to embed with key clients as a senior technical partner on their data science teams. This player-coach role blends rigorous predictive modeling with production engineering, shaping how organizations understand and predict user behavior and business outcomes.

You will work closely with client data science teams to tackle complex problems, in environments with imperfect data and evolving stakeholder needs.

Qualifications

• 7+ years of hands-on experience in predictive analytics, statistics, or ML.
• Fluency in predictive modeling methods including GLMs, econometrics, causal inference, and time-series.
• Strong software engineering fundamentals with production deployment, testing, and monitoring.
• Proficiency with SQL, Spark, and Python in production environments.
• Excellent communication and stakeholder management abilities.
• Graduate degree in a quantitative/behavioral field or equivalent experience.
• Based in the US or Canada.

Responsibilities

• Design, build, and validate predictive models from GLMs, causal/econometric methods to deep learning.
• Apply causal inference techniques to move stakeholders from correlation to actionable decisions.
• Own the full lifecycle of models from exploration to deployment, monitoring, and retraining.
• Work across the stack writing production-grade SQL, processing data at scale in Spark, and deploying models in Python.
• Collaborate with client teams to translate business questions into well-scoped modeling problems.
• Communicate technical work clearly to technical and non-technical stakeholders.
• Bring engineering discipline to a production environment to improve reliability and maintainability.

Skills

Predictive analytics

Statistical modeling

Causal inference

Time-series forecasting

Production deployment

Communication

Data storytelling

Education

MS or PhD in quantitative field

Tools

SQL

Spark

Python

Job description

About OneSix

OneSix is a leading data and artificial intelligence (AI) consultancy that helps businesses build the strategy, technology, and teams they need to scale growth and efficiency. Its team of skilled Data Engineers, Data Scientists, Machine Learning (ML) Experts, and AI Engineers seamlessly integrate with client teams to solve their most challenging business problems. Leveraging strategic partnerships with Snowflake, AWS, Matillion, Fivetran, Pyramid Analytics, and more, the company uses modern technology, scalable architectures, and industry best practices. With the recent acquisition of Strong Analytics, an ML and AI consultancy, OneSix is a uniquely powerful business partner to the enterprise, with a talent mix that is nearly impossible to find under one roof.

OneSix is a fast-growing firm with significant career opportunities for motivated professionals who want to help create a unique company. We are committed to fostering an inclusive employee experience that reflects the world we live in today. We’re an equal-opportunity employer that welcomes people regardless of backgrounds, experiences, abilities, and perspectives.

Lead Data Scientist

We're looking for a Lead Data Scientist to embed with key clients as a senior technical partner on their data science team. This is a player-coach role at the intersection of rigorous predictive modeling and production engineering: someone who is as comfortable deriving a causal estimate or specifying a generalized linear model as they are debugging a Spark job. You'll work closely with the client's data science team to shape how the organization understands and predicts user behavior and business outcomes. Success in this role depends as much on the strength of your judgment as your ability to earn trust in a room. Comfort in consulting work is also a requirement, working with production systems that have grown organically over years, data that isn't always clean, and business stakeholders who need answers on a timeline. You should find that kind of complexity energizing rather than draining.

What You’ll Do

• Design, build, and validate predictive models, from GLMs and causal/econometric methods to deep learning-based forecasting, to answer questions about user behavior, retention, and business performance.
• Apply causal inference techniques (quasi-experimental design, uplift modeling, propensity methods, and related econometric tools) to move client stakeholders beyond correlation and toward decisions they can act on with confidence.
• Own the full lifecycle of your models: from exploratory analysis and feature engineering through deployment, monitoring, and retraining in a live production environment.
• Work fluently across the stack, writing production-grade SQL, processing data at scale in Spark, and building and deploying models in Python to get from idea to shipped solution without waiting on a hand-off.
• Partner directly with the client's data science and broader analytics team, translating ambiguous business questions into well-scoped modeling problems and pushing back, respectfully and with evidence, when the data leads somewhere unexpected.
• Communicate technical work clearly to both technical and non-technical stakeholders, building the kind of credibility that earns you a seat at the table on strategic decisions, not just implementation ones.
• Bring engineering discipline to a production environment that is mature but imperfect, improving reliability and maintainability incrementally.

What You Bring

• 7+ years of hands-on experience in predictive analytics, applied statistics, or machine learning, with a track record of taking models from concept into production. (Strong candidates with somewhat less experience but exceptional depth are still encouraged to apply.)
• Deep fluency in predictive modeling techniques spanning generalized linear models, econometric methods, causal inference, and time-series forecasting, including deep learning-based forecasting approaches with the judgment to speak to trade-offs and failure modes from experience, not just theory.
• Strong software engineering fundamentals: you've deployed and maintained models in production, not just prototyped them in a notebook, and you're comfortable owning code quality, testing, and monitoring for the solutions you build.
• Proficiency across the modern data stack (e.g., SQL, Spark, and Python) and the judgment to work effectively in a production environment that's mature but occasionally messy, without losing momentum
• Excellent communication and interpersonal skills. You'll be working alongside smart technical leaders, and you need to be able to build trust quickly, hold your ground when you have good reason to, and adapt when you don't. Keen client/stakeholder capability is important.
• A graduate degree (M.S. or Ph.D.) in a quantitative or behavioral field ( statistics, economics, computer science, cognitive science, or a related discipline) or equivalent demonstrated experience.
• Based in the US or Canada.

Nice to Have

• Experience modeling user behavior as it relates to downstream outcomes like churn, lifetime value, engagement, or propensity to convert are all directly relevant.
• A Ph.D. in cognitive science, behavioral economics, or a similarly human-behavior-oriented quantitative field.
• Prior consulting or professional services experience, particularly in client-facing technical roles.

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 $180,000–$210,000 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.