[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:

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Exploratory Data Analysis (EDA):

• Conduct EDA and statistical profiling to identify trends and insights from data.

• Perform feature engineering specifically for time-series forecasting.

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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.

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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.

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Data Visualization:

• Create insightful data visualizations and dashboards using Amazon QuickSight or equivalent BI tools.

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Python Data Stack:

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

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Model Explainability:

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

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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

#LI-LO1

Our 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.