Experience developing agents / agentic infrastructure (e.g., Mosaic AI Agent Framework, agent orchestration, MCP). Preferably Mexico City (Santa Fe / Cuajimalpa). Although the position is not strictly on-site, we give preference to candidates based in Mexico City; however, we are open to other locations. 🎁 PerksRead the full posting
Formalize the trade-off between service cost and revenue per point of sale as an optimization function
Model the cost and profitability layer that feeds customer segmentation and service model assignment
Build and solve linear, integer and constrained optimization models for each customer's service model
Develop customer characterization pillars and extend them across multiple countries
Document assumptions and validate results with business and finance stakeholders
Formalize mathematically the trade-off between service time / RTM cost and revenue per point of sale
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.
Document assumptions and validate results with business and finance stakeholders.
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From 10,289 similar postings that came down, and 15 of Muttdata’s. Coming down is not always a hire.
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- Financial context: ability to interpret a P&L and translate it into variables, costs, and objective functions. - Advanced Python, including optimization libraries (PuLP, Pyomo, OR-Tools, or similar). - Solid foundations in statistics and modeling.
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- 💪 Wellhub or sports club stipend to stay active - 🚀 AWS, DBT, Google Cloud, Azure & Databricks certifications fully covered - 🍕 Food credits via Pedidos Ya – because great work deserves great food.
- Astronomer - Databricks 🌟 Our Values
- 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.
- Solid foundations in statistics and modeling. - Hands-on experience with Databricks. - Ability to translate business needs into analytical solutions and communicate complex findings clearly to technical and non-technical audiences.
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New Data Scientist postings at the employers we follow are down 3% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.
🚀 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
Remote - Latam
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Argentina
🚀 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.
- Experience developing agents / agentic infrastructure (e.g., Mosaic AI Agent Framework, agent orchestration, MCP). - Preferably Mexico City (Santa Fe / Cuajimalpa). Although the position is not strictly on-site, we give preference to candidates based in Mexico City; however, we are open to other locations. 🎁 Perks - 🌍 Remote-first culture – work from anywhere! - 🚀 In-Company English Lessons.
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