[Job-29268] Machine Learning Engineering, Colombia

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

AWS Certified Cloud Practitioner

AWS Certified Data Engineer – Associate

AWS Certified Machine Learning – Associate or AWS Certified Machine Learning – Specialty

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\nOur benefits include:

• 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.

Collaboration is our superpower, diversity unites us, and excellence is our standard.
We value diverse identities and life experiences, fostering a diverse, inclusive, and safe work environment. We encourage applications from diverse and underrepresented groups to our job positions.

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