At Birdman, we are building one of the fastest-growing plant-based brands.
Our mission is to make healthy, sustainable, and high-performance nutrition accessible through products that are better for people and the planet.

As we scale across channels, markets, and geographies, we are building a stronger data and analytics foundation to support better, faster, and more reliable business decisions.

The Role
We are looking for a Data Scientist to join our Revenue Growth Management team.
This is a highly technical, high-impact role focused on building the statistical and machine learning foundation behind commercial decision-making.
You will work on problems such as demand forecasting, pricing, promotional effectiveness, and customer segmentation, translating business questions into analytical models and model outputs into business insights.
This role is adecuado for someone who is hands‑on with data, comfortable working end-to-end (from pipelines to models to insights), and motivated to raise the analytical standard of the business.

Impact & Ownership

Build and scale the statistical and ML foundation for revenue analytics
Improve forecast accuracy, pricing decisions, and promotional ROI measurement
Reduce manual work through automated Python pipelines and reusable frameworks
Ensure analytical outputs are reliable, reproducible, and trusted
Accelerate analytical workflows using AI tools (ChatGPT, Claude)

Contribute to the development of the company's Revenue Data Lake

Responsibilities

Build and maintain statistical and machine learning models (forecasting, elasticity, incrementality, segmentation)




Develop and maintain Python data pipelines connecting ERP, retail portals, and internal systems
Design and execute A/B tests and quasi-experiments with statistical rigor
Perform data validation, model validation, and quality checks before stakeholder use
Build and maintain Power BI dashboards with advanced data models
Collaborate with strategy and commercial teams on data-driven projects
Leverage AI tools to improve speed and quality of analysis

Document models and pipelines to ensure reproducibility and scalability

Requirements

1. 4 years in data science, quantitative analytics, or similar roles

Hands‑on experience building models used in real business environments

Experience in CPG, retail, eCommerce, or marketplaces is a strong plus

Skills

Advanced Python (pandas, numpy, scikit-learn, statsmodels)
Advanced SQL (CTEs, window functions, optimization)
Strong statistical foundation (regression, time series, hypothesis testing, causal inference)
Machine learning experience (classification, clustering, gradient boosting)
Experience building data pipelines and working with multiple data sources
Power BI (intermediate to advanced)

Strong problem-solving and structured thinking

Language & Location

Professional English required

Based in Guadalajara or willing to relocate

Nice to Have

Experience with PySpark, Databricks, or Microsoft Fabric
MLOps basics and version control (Git)
Experience with APIs (Airflow, dbt)
Experience in consulting or advanced analytics teams

Exposure to Bayesian methods or advanced experimentation

Ready to take flight?

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📌 Revenue Data and Business Sr. Analyst (Guadalajara)
🏢 Birdman
📍 Guadalajara