About this # 6 Data Scientist Senior – Customer Segmentation & Classification (RTM) role at Muttdata
🚀 Join Our Remote Data Products & Machine Learning Startup! 🚀
At Muttdata, we build innovative Data Products and Machine Learning solutions that help companies solve complex business challenges. As a fast-growing, remote-first startup, we’re passionate about technology, collaboration, and continuous learning.
We are looking for an Data Scientist Senior – Customer Segmentation & Classification (RTM) to join our team 🐶🚀. In this role, you will develop the RTM (Route-to-Market) customer characterization models, translating an end-to-end understanding of the P&L into a formal optimization function that determines the optimal service model for each customer based on profitability, cost-to-serve, and potential.
This role sits at the intersection of operations research, finance, and commercial strategy. Today, the trade-off between service time and revenue per point of sale is handled heuristically. Your mission is to formalize it mathematically and make it scalable across countries. You will work closely with business and finance stakeholders, as well as Data Engineers and Analytics Engineers. Strong analytical rigor, ownership, and the ability to communicate with non-technical audiences are essential
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Responsibilities 🤓
- Formalize mathematically the trade-off between service time / RTM cost and revenue per point of sale, building the optimization function that currently operates heuristically.
- Model the cost and profitability layer (visit drivers, RTM Size thresholds, minimum margin) that feeds the segmentation and the assignment of service models.
- Build and solve optimization models (linear/integer programming, constrained optimization) to determine the optimal service model for each customer.
- Work on the Characterization pillars (Channel, Size, Potential, Territorial Profile, Digital Autonomy) and their multi-country expansion.
- Interpret the P&L end-to-end and translate it into decision variables, costs, and objective functions.
- Document assumptions and validate results with business and finance stakeholders.
- Develop analyses, features, and models on Databricks, collaborating with Data Engineers and Analytics Engineers.
- Promote best practices in modeling, reproducibility, and documentation across the team.
