Remote Data Scientist - Growth & Causal ML (Semi Senior)

Lever, Inc.; United States; Remote; USD 110,000 - 170,000; Full time

Benefits offered by this job

Remote-first culture

In-Company English Lessons

AWS, Databricks certs covered

Food credits viaPedidos Ya

Birthday off + extra vacation week

Job summary

Muttdata, a remote-first data science startup, is seeking a Data Scientist Semi Senior to measure what works in growth and marketing for a major beverage client in Mexico. You’ll design experiments, estimate causal impact, and turn results into decisions that drive acquisition, retention, and revenue.

Join a cross-functional team collaborating with marketing, growth, and data engineers to move beyond correlations and answer questions about campaigns, promotions, and budget allocation.

Qualifications

• 3+ years in Data Science, statistics, econometrics, or similar roles.
• Hands-on Databricks experience required.
• Experience designing and analyzing online/offline experiments.
• Strong knowledge of causal inference methods and their practical use.

Responsibilities

• Design, run, and analyze A/B tests and multivariate experiments.
• Apply causal inference techniques to estimate marketing campaign impact.
• Measure marketing performance: incrementality, attribution, ROAS, CLV.
• Translate growth questions into analytical problems and experiments.
• Develop analyses and models on Databricks with data engineers.

Skills

A/B testing design

Causal inference

Python (pandas, PySpark, statsmodels,

Education

Economics/Statistics/Quantitative field degree

Tools

Databricks

Spark/PySpark

Delta Lake

SQL

Job description

Muttdata, a remote-first data science startup, is seeking a Data Scientist Semi Senior to measure what works in growth and marketing for a major beverage client in Mexico. You’ll design experiments, estimate causal impact, and turn results into decisions that drive acquisition, retention, and revenue.

Join a cross-functional team collaborating with marketing, growth, and data engineers to move beyond correlations and answer questions about campaigns, promotions, and budget allocation.