[Job-29268] Machine Learning Engineering, Colombia

🇨🇴 Colombia, CO, CO On-site Posted May 14, 2026

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WorkplaceOn-site

LanguageEnglish

PostedMay 14, 2026

Last verifiedMay 14, 2026

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2 locations

Colombia

Colombia, CO
CO

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Key details: 2 locations, On-site
Current openings: 192 active jobs
Original language: English
Source and freshness: Collected from public career pages and reviewed through JobGrid.eu source availability checks. Last verified: May 14, 2026.
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We are tech transformation specialists, uniting human expertise with AI to create scalable tech solutions. With over 8,000 CI&Ters around the world, we’ve built partnerships with more than 1,000 clients during our 30 years of history. Artificial Intelligence is our reality. We are looking for a Data & Analytics Engineer supporting an AI/ML implementation for demand forecasting and resource optimization in the public transportation / fare collection industry. Works alongside an AWS ProServe ML Specialist on EDA, feature engineering, capacity modeling, and operational dashboards. Responsibilities: Exploratory Data Analysis (EDA): Conduct EDA and statistical profiling to identify trends and insights from data. Perform feature engineering specifically for time-series forecasting. Data Wrangling and Preparation: Extract and transform data from relational databases (RDS, Oracle, PostgreSQL) into analytics-ready formats. Develop pipelines for data ingestion and processing. Machine Learning Modeling: Build classical ML models for time-series forecasting, regression, and capacity/throughput modeling. Evaluate model performance using metrics such as RMSE, MAE, and MAPE, documenting performance results. Data Visualization: Create insightful data visualizations and dashboards using Amazon QuickSight or equivalent BI tools. Python Data Stack: Utilize the Python data stack (pandas, NumPy, scikit-learn, matplotlib/seaborn) for data manipulation and analysis. Model Explainability: Apply SHAP or other model explainability techniques to interpret model outputs. Collaboration and Communication: Work closely with stakeholders to translate business rules into effective feature engineering pipelines. Engage in milestone-driven, Firm Fixed Price delivery models, ensuring timely project completion. Requirements for this challenge: 4+ years in data engineering or applied data science roles, preferably with experience on AWS. Proficient in exploratory data analysis (EDA), statistical profiling, and feature engineering for time-series forecasting. Experience in data wrangling from relational databases (RDS, Oracle, PostgreSQL) into analytics-ready formats. Strong understanding of classical ML modeling techniques, including time-series forecasting and regression. Familiarity with model evaluation metrics (RMSE, MAE, MAPE) and performance documentation. Experience in data visualization and dashboard development using Amazon QuickSight or equivalent BI tools. Hands-on experience with Amazon SageMaker (training, evaluation, Clarify). Proficient in the Python data stack, including pandas, NumPy, scikit-learn, matplotlib, and seaborn. Working knowledge of SQL and dimensional modeling. Familiarity with SHAP or model explainability techniques is a plus. Expected Certifications