Machine Learning Engineer

📋 Description

• Conduct exploratory data analysis (EDA) and statistical profiling to uncover trends and insights from data.

• Execute feature engineering specifically tailored for time-series forecasting.

• Extract and transform data from relational databases (RDS, Oracle, PostgreSQL) into formats ready for analytics.

• Develop pipelines for data ingestion and processing.

• Construct classical machine learning models for time-series forecasting, regression, and capacity/throughput modeling.

• Assess model performance using metrics such as RMSE, MAE, and MAPE, while documenting performance results.

• Generate insightful data visualizations and dashboards utilizing Amazon QuickSight or similar BI tools.

• Employ the Python data stack (pandas, NumPy, scikit-learn, matplotlib/seaborn) for data manipulation and analysis.

• Implement SHAP or other model explainability techniques to interpret model outputs.

• Collaborate closely with stakeholders to convert business rules into effective feature engineering pipelines.

• Participate in milestone-driven, Firm Fixed Price delivery models to ensure timely project completion.

⛳️ Requirements

• Over 4 years of experience in data engineering or applied data science roles, preferably with a background in AWS.

• Proficient in exploratory data analysis (EDA), statistical profiling, and feature engineering for time-series forecasting.

• Experienced in data wrangling from relational databases (RDS, Oracle, PostgreSQL) into analytics-ready formats.

• Strong understanding of classical machine learning modeling techniques, including time-series forecasting and regression.

• Familiarity with model evaluation metrics (RMSE, MAE, MAPE) and the documentation of performance results.

• Proficient in data visualization and dashboard creation using Amazon QuickSight or equivalent BI tools.

• Hands-on experience with Amazon SageMaker (training, evaluation, Clarify).

• Well-versed in the Python data stack, including pandas, NumPy, scikit-learn, matplotlib, and seaborn.

• Knowledge of SQL and dimensional modeling.

• Familiarity with SHAP or model explainability techniques is advantageous.

🏝️ Benefits

• Premium Healthcare

• Meal voucher

• Maternity and Parental leaves

• Mobile services subsidy

• Sick pay-Life insurance

• CI&T University

• Colombian Holidays

• Paid Vacations

• And many others.