#3 - Data Scientist Senior - Causal Inference

Remote

San Francisco (CA)

Remote

USD 180,000 - 240,000

Full time

11 days ago

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Benefits offered by this job

Remote-first culture
English Lessons
Wellhub or sports club stipend
AWS, DBT, Google Cloud, Azure & Databr
Databricks certifications covered
Food credits via Pedidos Ya
Birthday off
Referral bonuses
Annual Mutters' Trip
Monthly childcare reimbursement

Job summary

Muttdata, a remote-first data science startup, builds data products and ML solutions for business challenges. You will lead analytical work on a key engagement with a beverage company in Mexico, measuring what works in growth and marketing and driving decisions that boost acquisition, retention, and revenue.

The role sits at the intersection of statistics, econometrics, and marketing, collaborating with marketing, growth, and engineering teams to move beyond correlations and quantify causal

Qualifications

  • 3+ years in Data Science or similar analytical roles.
  • Hands-on Databricks experience (notebooks, Spark/PySpark, Delta Lake).
  • Design and analysis of A/B tests and experiments.
  • Strong knowledge of causal inference methods and practical use.
  • Solid statistics/econometrics foundations (hypothesis testing, regression).
  • Proficiency in Python and SQL; experience in marketing/growth analytics.
  • Experience applying DS to growth, marketing, or commercial problems.

Responsibilities

  • Design, run, and analyze A/B tests and multivariate experiments.
  • Apply causal inference methods to estimate marketing impact.
  • Measure marketing performance: incrementality, ROI/ROAS, CLV, MMM.
  • Translate business questions into analytical problems and experiments.
  • Develop analyses and models on Databricks with data engineers.
  • Build predictive/segmentation models for targeting and personalization.

Skills

A/B testing
Causal inference
Statistics & econometrics
Python (pandas, PySpark, scikit-learn)
SQL
Growth/marketing analytics
Databricks platform

Education

Bachelor's degree in Economics, Statistics, or related field

Tools

Databricks
PySpark
Spark
Delta Lake

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 analytical, curious, and business-minded Data 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.
Our Partnerships
  • Amazon Web Services
  • Astronomer
  • Databricks
Our Values
  • We are Data Nerds
  • We are Open Team Players
  • We Take Ownership
  • We Have a Positive Mindset
Responsibilities
  • 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, customer lifetime value (CLV), and marketing mix modeling (MMM).
  • Translate business questions from growth and marketing teams into well-defined analytical problems and experimental designs.
  • Develop analyses, features, and models on Databricks (notebooks, Spark, Delta Lake), collaborating with Data Engineers and Analytics Engineers on data pipelines and analytical datasets.
  • Build predictive and segmentation models (churn, propensity, customer segmentation) that support targeting and personalization strategies.
Required Skills
  • 3+ years of experience in Data Science, Applied Statistics, Econometrics, or similar analytical roles.
  • Hands-on experience with Databricks (notebooks, Spark/PySpark, Delta Lake) – required.
  • Solid, hands-on experience designing and analyzing A/B tests and online/offline experiments.
  • Strong knowledge of causal inference methods and their assumptions, limitations, and practical application (DiD, Synthetic Control, Matching, IV, uplift, etc.).
  • Strong foundations in statistics and econometrics (hypothesis testing, regression, Bayesian and frequentist approaches, time series).
  • Proficiency in Python (pandas, PySpark, statsmodels, scikit-learn) and advanced SQL.
  • Experience applying data science to growth, marketing, or commercial problems (campaign measurement, pricing, promotions, customer analytics).
Nice to Have Skills
  • Degree in Economics, Econometrics, Statistics, or related quantitative fields (ideally with a focus on applied microeconomics or causal inference).
  • Experience in CPG, retail, consumer goods, or beverage industries.
  • Experience with Marketing Mix Modeling (e.g., Meridian, Robyn, PyMC-Marketing) and media attribution.
  • Experience with causal libraries (DoWhy, EconML, CausalML) and Bayesian modeling (PyMC, Stan).
  • Experience with MLflow and Databricks workflows/jobs.
Perks
  • 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
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