ML Engineer

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

📋 Description

• Develop predictive models (including forecasting, time series analysis, and trend analysis) using real-world program and financial data.

• Create anomaly and outlier detection systems to identify risks, inefficiencies, and subtle patterns.

• Take ownership of feature engineering, model evaluation, and interpretability (including feature importance and SHAP-style analysis).

• Engage in the entire process from data exploration to modeling and delivering business-facing insights.

• Collaborate with product and analytics teams to transform models into actionable decisions.

⛳️ Requirements

• 4–7 years of experience as a Machine Learning Engineer or Applied Data Scientist.

• Strong background in predictive modeling and anomaly detection.

• Practical experience handling messy, high-volume financial or program data.

• Solid statistical intuition beyond merely fitting models.

• Proficiency in Python, including libraries such as Pandas, NumPy, and scikit-learn.

• Ability to work independently as a senior individual contributor.

• Familiarity with U.S. healthcare-adjacent data (such as insurance, benefits, copay, and utilization) is a plus.

• Experience in compliance-sensitive environments (like HIPAA-constrained data) is a plus.

• Ability to translate models into dashboards, reports, or insights suitable for executives is a plus.

• Experience with XGBoost, LightGBM, and strong SQL skills are a plus.

🏝️ Benefits

• Health insurance

• Flexible work arrangements

• Professional development