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 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 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 ClickHouse;
- Experience collaborating with backend engineering teams using containerized workflows or modern package ecosystems.
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.
About the role
The benefits of joining us
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.
Your AgileEngine journey starts here
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