Senior ML Engineer

This is a fully remote position, open to applicants in Mexico.

📋 Description

• Analyze extensive datasets to uncover trends, patterns, and actionable insights for the business.

• Develop and maintain data models, transformations, and pipelines utilizing SQL and dbt.

• Work collaboratively with stakeholders to establish metrics, KPIs, and reporting specifications.

• Uphold data governance to ensure data quality, integrity, and accessibility throughout the organization.

• Document processes, workflows, and analytical results for cross-functional collaboration.

• Design, construct, and assess supervised and unsupervised machine learning models (classification, regression, clustering, forecasting).

• Facilitate discussions with stakeholders to translate business inquiries into machine-learning-ready problem statements.

• Execute feature engineering, selection, and transformation to prepare data for model training.

• Validate and convey model performance using suitable evaluation metrics (AUC, RMSE, F1, precision/recall, etc.).

• Assist in lightweight model deployment and monitoring, identifying performance drift and suggesting retraining triggers.

• Contribute to experiment design and A/B testing methodologies as needed.

⛳️ Requirements

• Minimum of 5 years of experience in Data Analytics, Data Science, or a combined analytics and ML position.

• Proven experience in building and deploying machine learning models within a business context, beyond academic or exploratory projects.

• Strong analytical and problem-solving skills with the capability to convert complex data into clear, actionable insights.

• Exceptional communication abilities to effectively engage with both technical and non-technical stakeholders.

• Proficiency in Python for both data wrangling and ML model development, including libraries such as pandas, NumPy, matplotlib, seaborn, and ML libraries like scikit-learn, XGBoost, LightGBM, or equivalent.

• Strong SQL expertise, encompassing querying, optimization, and data modeling.

• Experience with dbt for constructing and version-controlling data transformations.

• Solid grasp of relational databases and data warehouse principles.

• Comfort with statistical reasoning, including distributions, hypothesis testing, regression, and uncertainty quantification.

🏝️ Benefits

• Competitive compensation

• Remote-first lifestyle

• Career growth opportunities across various industries and technologies