Senior Data Scientist

About the Role

Senior Data Scientist to lead the implementation of a Marketing Mix Modeling framework into a cross-channel optimization product, building client-specific MMM models using Bayesian frameworks including Meridian and Robin. You will develop scalable, production-ready models using Python, SQL, and AWS infrastructure, design human-in-the-loop feedback systems to improve model accuracy over time, and collaborate with MLOps teams to define the foundational infrastructure for ML deployment. The role requires 5+ years of data science experience with autonomous, end-to-end model ownership. What You'll Do

• Develop and scale client-specific Marketing Mix Modeling (MMM) models using Meridian or Robin rather than a single monolithic model

• Build pragmatic baseline models to handle noisy marketing data and thin data tiers for new clients

• Treat ML training as an operations problem by utilizing AWS tools to train and deploy models

• Collaborate with internal MLOps teams to define the foundational infrastructure for deploying machine learning models to production

• Lead implementation of MMM framework into a cross-channel optimization product

• Develop scalable, production-ready models using Python, SQL, and AWS infrastructure

• Design human-in-the-loop feedback systems to improve model accuracy over time

• Own end-to-end model development and deployment lifecycle What We're Looking For

• 5+ years of commercial data science experience with a proven track record of operating autonomously

• Experience building and maintaining machine learning models, including choosing the approach, shaping the data, diagnosing problems, and iterating

• Demonstrated experience with Bayesian frameworks such as PyMC or Stan, or Marketing Mix Modeling (MMM) tooling

• Strong proficiency in Python and SQL

• Solid experience building and deploying models using AWS infrastructure such as SageMaker Studio or EC2

• Strong foundation working with relational databases such as PostgreSQL or MySQL to pull, clean, and manipulate large data tiers

• Upper-intermediate English level Nice to Have

• Deep customization experience with Google Meridian

• Experience building or designing human-in-the-loop machine learning workflows

• Exposure to cloud data lakes and analytical databases such as AWS Athena or ClickHouse

• Experience collaborating with backend engineering teams using containerized workflows or modern package ecosystems Compensation & Benefits

• Professional growth: Accelerate your professional journey with mentorship, TechTalks, and personalized growth roadmaps

• Competitive compensation: We match your ever-growing skills, talent, and contributions with competitive USD-based compensation and budgets for education, fitness, and team activities

• A selection of exciting projects: Join projects with modern solutions development and top-tier clients that include Fortune 500 enterprises and leading product brands

• Flextime: Tailor your schedule for an optimal work-life balance, by having the options of working from home and going to the office – whatever makes you the happiest and most productive.