Senior Data Scientist; MMM

Senior Data Scientist

Agile Engine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards. If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!

About The Role

We are looking for a 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 Will 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.

Must Haves

• 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 Sage Maker 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 Haves

• 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 Click House;
• Experience collaborating with backend engineering teams using containerized workflows or modern package ecosystems.

Perks And Benefits

• Professional growth:
  Mentorship, Tech Talks, and personalized growth roadmaps.
• Competitive compensation: USD-based pay with education, fitness, and team activity budgets.
• Exciting projects:
  Modern solutions with Fortune 500 and top product companies.
• Flextime:
  Flexible schedule with remote and office options.