Senior Data Scientist
Summary
Senior Data Scientist in Mexico City builds and validates statistical models in Python and PySpark to solve business problems, collaborating with ML engineers using cloud and MLOps tools.
We're not just looking for talent; we're looking for curious minds that enjoy learning and shaping the future.
We're a demanding technology company, and yes, we move fast. But nobody competes alone. We work as a team, and if you're looking for challenges that push you out of your comfort zone (because you don't grow there), you're in the right place. Here, you'll learn from experts, participate in high-impact projects, and always be at the forefront of technology.
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About the Role
We are looking for a Senior Data Scientist with a solid statistical background and practical experience delivering data science projects in business environments.
In this role, you will frame complex business challenges into formal modeling problems, execute rigorous research cycles, and deliver reproducible solutions designed for seamless integration by engineering teams. You will work in close collaboration with ML Engineers; therefore, we expect clear judgment regarding role boundaries within the ecosystem and the discipline to adhere to strict software engineering standards—beyond basic analytical practices.
What We Are Looking For
Technical Fundamentals
Primary Language: Advanced mastery of Python as your primary development language.
DS & ML Ecosystem: Solid expertise in Scikit-Learn, XGBoost, LightGBM, Pandas, Polars, Statsmodels, and SciPy.
Deep Learning: Hands-on experience with TensorFlow or PyTorch (when the problem complexity justifies it).
Data at Scale: Advanced SQL and PySpark for scalable data exploration and transformation.
Cloud Infrastructure: Familiarity with cloud storage and data handling (GCS, Azure Blob Storage).
Statistical Rigor
Experimental Design: Hypothesis testing and experimental design applied directly to business problems.
Causal Inference: Deep understanding of causality—distinguishing correlation from cause and applying appropriate causal techniques.
Robust Validation: Evaluation beyond simple accuracy, focusing on business metrics, bias analysis, and subgroup behavior.
Development Discipline
Version Control: Professional, daily use of Git as a fundamental part of your workflow.
Clean Code: Production of organized, modular Python code—delivering production-ready scripts, not just exploratory notebooks.
Experimentation: Experience with experiment tracking tools (e.g., MLflow) to ensure full traceability.
Documentation: Ability to structure comprehensive model documentation (problem statement, data lineage, limitations).
Engineering Standards: Adherence to team protocols regarding secure credential handling, data versioning, and project architecture.
AI & LLM Judgment
Pragmatic AI Use: Responsible use of Generative AI coding assistants, backed by critical evaluation and validation of generated output.
Architectural Judgment: Clear discernment on when agentic systems/LLMs are the right solution—and when traditional ML approaches are superior.
Background & Experience
5+ years in data science, statistical analysis, or applied research roles.
Proven track record of end-to-end projects—from initial problem definition to final validated model delivery.
Strong history of collaborating with ML Engineers and Data Engineers in Agile environments.
Demonstrable code repositories (a shareable portfolio or GitHub profile is highly valued).
Academic Background
Master’s or Ph.D. in Mathematics, Statistics, Actuarial Science, Physics, Computer Science, or related quantitative fields.
Prior experience in academic or applied research is a strong plus.
What do we offer?
We support your personal and professional growth with individualized development plans, where you decide your career path and how far you want to go.
More vacation days than required by law: You don't have to wait a year to enjoy your vacation, plus additional days for special events and holidays.
Finances beyond your salary: Supermarket vouchers, savings fund, training opportunities, wellness bonus, collaborations, and discounts.
Emotional support is our priority. We want you to have peace, both physical and mental, which is why we offer a variety of benefits that support your personal well-being and the health of your family. We want to take care of you and your loved ones!
There's room here for good people... like you. We want to get to know you!