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#3 - Data Scientist Senior - Causal Inference - Databricks
- Pay
- Pay not listed
- Work setting
Remote — work setting source
Listed location: Remote
Read the full posting- Employment
- Not stated
What you’ll work on
Full postingDesign, run and analyze A/B tests and multivariate experiments
Estimate impact of campaigns, promotions and pricing using causal methods
Measure marketing incrementality, ROI/ROAS, CLV and marketing mix
Turn business questions into analytical problems and experiment designs
Build churn, propensity and segmentation models for targeting
From the employer’s posting
Design, run, and analyze A/B tests and multivariate experiments
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
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.
Build predictive and segmentation models (churn, propensity, customer segmentation) that support targeting and personalization strategies.
What you’ll bring
All qualificationsCore experience
- 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.
- Strong knowledge of causal inference methods and their assumptions, limitations, and practical application (DiD, Synthetic Control, Matching, IV, uplift, etc.).
- 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).
- Degree in Economics, Econometrics, Statistics, or related quantitative fields (ideally with a focus on applied microeconomics or causal inference).
Qualification wording
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.
Strong knowledge of causal inference methods and their assumptions, limitations, and practical application (DiD, Synthetic Control, Matching, IV, uplift, etc.).
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).
Degree in Economics, Econometrics, Statistics, or related quantitative fields (ideally with a focus on applied microeconomics or causal inference).
Posting record
Report an errorActively hiringFirst seen by us 8 days ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Oct 27, 20268 days ago
- Recorded sightings
- 9
- Last seen by us
- Nov 3, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Muttdata is hiring
29 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Data Scientist hiring is picking up
- Takes jobs down at a usual pace
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- SQL
- AWS
- Azure
- Databricks
- dbt
- Delta Lake
- MLflow
- Spark
- pandas
- PySpark
- scikit-learn
- GCP
Where the posting names them
- 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).
🌟 Our Partnerships - Amazon Web Services - Astronomer
- 💪 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
- 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.
- 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.
- Experience with causal libraries (DoWhy, EconML, CausalML) and Bayesian modeling (PyMC, Stan). - Experience with MLflow and Databricks workflows/jobs. 🎁 Perks
Your next step
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Has Muttdata posted this job before?
Yes. We’ve followed one other #3 - Data Scientist Senior - Causal Inference - Databricks job there since October 2026. It is still up.
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
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
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Remote
🚀 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.
More source context
🎁 Perks - 🌍 Remote-first culture – work from anywhere! - 🚀 In-Company English Lessons.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.