# 6 Data Scientist Senior – Customer Segmentation & Classification (RTM) - Latam

Mutt Data; United States; Remote; USD 150,000 - 210,000; Full time

Benefits offered by this job

Remote-first culture

In-Company English Lessons

Wellbeing stipend

Certifications covered (AWS/Databricks

Job summary

Muttdata, a remote-first data science startup, seeks a Senior Data Scientist – Customer Segmentation & Classification (RTM) to formalize the trade-offs between service time, cost-to-serve, and profitability to determine optimal service models across countries.

You will collaborate with business and finance stakeholders, data engineers, and analytics engineers to translate end-to-end P&L into actionable models, emphasizing rigor, ownership, and clear communication to non-technical audiences.

Qualifications

• Experience in Operations Research and optimization (linear and integer programming).
• Ability to translate a P&L into variables, costs and objective functions.
• Advanced Python with optimization libraries (PuLP, Pyomo, OR-Tools).
• Strong foundations in statistics and modeling.
• Hands-on experience with Databricks.
• Translate business needs into analytical solutions and communicate clearly to non-technical audiences.
• Experience with survival models / CLV and econometrics.
• Experience in retail or consumer goods (CPG).
• Experience developing agents / agent frameworks.

Responsibilities

• Formalize mathematically the trade-off between service time and RTM cost and revenue per POS, building the optimization function.
• Model the cost and profitability layer feeding segmentation and service-model assignment.
• Build and solve linear/integer programming models to determine the optimal service model for each customer.
• Work on the Characterization pillars (Channel, Size, Potential, Territorial Profile) and multi-country expansion.
• Interpret the P&L end-to-end and translate into decision variables, costs and objectives.
• Document assumptions and validate results with business and finance stakeholders.
• Develop analyses, features, and models on Databricks with Data & Analytics Engineers.
• Promote best practices in modeling, reproducibility, and documentation.

Skills

Operations Research

Python proficiency

Databricks

Optimization libs

Econometrics

Statistical modeling

P&L interpretation

Retail/CPG experience

AI agent frameworks

Tools

PuLP

Pyomo

OR-Tools

Databricks

AWS / GCP / Azure

Job description

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.

What we do

• Leveraging our expertise, we build modern Machine Learning systems for demand planning and budget forecasting.
• Developing scalable data infrastructures, we enhance high-level decision-making, tailored to each client.
• Offering comprehensive Data Engineering and custom AI solutions, we optimize cloud-based systems.
• Using Generative AI, we help e-commerce platforms and retailers create higher-quality ads, faster.
• Building deep learning models, we enhance visual recognition and automation for various industries, improving product categorization, quality control, and information retrieval.
• Developing recommendation models, we personalize user experiences in e-commerce, streaming, and digital platforms, driving engagement and conversions.

Our Technology Stack

• Amazon Web Services
• Astronomer
• Databricks

Company Values

• We are Data Nerds
• We are Open Team Players
• We Take Ownership
• We Have a Positive Mindset

Check out our case studies and dive into our blog post to learn more about our culture and the exciting projects we’re working on!

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.

Requirements

• Background and experience in Operations Research / Optimization (linear and integer programming, constrained optimization).
• 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.
• Hands-on experience with Databricks.
• Ability to translate business needs into analytical solutions and communicate complex findings clearly to technical and non-technical audiences.
• Experience with survival models / CLV and econometrics.
• Experience in retail or consumer goods (CPG).
• 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.

Benefits

• Remote-first culture – work from anywhere!
• In-Company English Lessons.
• 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.
• Birthday off + an extra vacation week (Mutt Week! )
• Referral bonuses – help us grow the team & get rewarded!
• Annual Mutters' Trip – an unforgettable getaway with the team!
• Monthly Childcare Reimbursement – Because supporting families matters too