Machine Learning Engineer

CI&T

Data & Analytics Engineer creating tech solutions for demand forecasting and resource optimization. Collaborating with AWS ProServe on EDA, feature engineering, and operational dashboards.

Posted 5/14/2026full-timeRemote • 🇨🇴 ColombiaMid-LevelSeniorWebsite

Tech Stack

Tools & technologies

AWSNumpyOraclePandasPostgresPythonScikit-LearnSQL

About the role

Key responsibilities & impact

Conduct EDA and statistical profiling to identify trends and insights from data.
Perform feature engineering specifically for time-series forecasting.
Extract and transform data from relational databases (RDS, Oracle, PostgreSQL) into analytics-ready formats.
Develop pipelines for data ingestion and processing.
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.
Create insightful data visualizations and dashboards using Amazon QuickSight or equivalent BI tools.
Utilize the Python data stack (pandas, NumPy, scikit-learn, matplotlib/seaborn) for data manipulation and analysis.
Apply SHAP or other model explainability techniques to interpret model outputs.
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

What you’ll need

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.

Benefits

Comp & perks

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.

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

exploratory data analysisstatistical profilingfeature engineeringtime-series forecastingclassical ML modelingdata wranglingmodel evaluation metricsdata visualizationdashboard developmentdimensional modeling

Soft Skills

stakeholder engagementproject completion