Data Scientist Senior

Writing; México; Remote; MXN 1,200,000 - 1,800,000; Full time

Job summary

MUTT DATA is a remote-first startup delivering data products and ML solutions for a beverage company client in Mexico. We seek a Senior Data Scientist to design experiments, estimate causal impact, and translate results into actionable growth and revenue decisions.

You will collaborate with marketing, growth, and analytics engineers to move beyond correlations and drive customer acquisition and retention. The role sits at the intersection of statistics, economics, and marketing, requiring

Qualifications

• Proven ability to design experiments and estimate causal impact.
• Experience applying causal inference techniques to marketing and growth.
• Strong communication of complex results to non-technical audiences.

Responsibilities

• Design, run, and analyze A/B tests and multivariate experiments.
• Apply causal inference techniques to estimate campaign impact when randomization is not possible.
• Measure and optimize marketing performance, attribution, and ROI/ROAS.

Skills

Causal inference

Experiment design

A/B testing

Data analysis

Communication to non-technical

Education

Economics or quantitative field

Tools

AWS

Astronomer

Databricks

Job description

#3 - Data Scientist Senior - Causal Inference at MUTT DATA

Senior Remote Posted 1 day ago RemoteFirstJobs Product

Senior Remote Posted 1 day ago RemoteFirstJobs Product Data Analytics

AI summary:Senior Data Scientist designs and analyzes experiments to measure causal impact on marketing, growth, and revenue decisions for a beverage company client.

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 analytical, curious, and business-mindedData Scientist Senior to join one of our key engagements with a leading beverage company in Mexico. You will be the go-to person for measuring what really works in growth and marketing: designing experiments, estimating causal impact, and turning the results into decisions that drive customer acquisition, retention, and revenue.

This role sits at the intersection of statistics, economics, and marketing. You will work closely with marketing, growth, and commercial stakeholders, as well as with Data Engineers and Analytics Engineers, to move beyond correlations and answer questions like “Did this campaign actually cause an increase in sales?” or “Which promotions and channels deserve more budget?”. A strong analytical profile, methodological rigor, and the ability to communicate findings to non-technical audiences are essential. A background in Economics (or similar quantitative fields) is highly valued.

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.
• Amazon Web Services
• Astronomer
• Databricks
• We Take Ownership
• We Have a Positive Mindset

Curious about what we’re up to? 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!

• Design, run, and analyze A/B tests and multivariate experiments (sample size and power calculations, randomization, guardrail metrics, interpretation of results).
• Apply causal inference techniques (Difference-in-Differences, Synthetic Control, Propensity Score Matching, Instrumental Variables, Regression Discontinuity, uplift modeling) to estimate the impact of marketing campaigns, promotions, pricing, and loyalty initiatives when randomization is not possible.
• Measure and optimize marketing performance: incrementality, attribution, ROI/ROAS,