Machine Learning Engineer

🕒 May 14

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CI&T

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

Founded 1995

🤖 Artificial Intelligence

☁️ SaaS

💰 $5.5M Venture Round on 2014-04

Artificial Intelligence • Cloud Services • SaaS

CI&T is a global tech transformation specialist focusing on helping organizations navigate their technology journey. With services spanning from application modernization and cloud solutions to AI-driven data analytics and customer experience, CI&T empowers businesses to accelerate their growth and maximize operational efficiency. The company emphasizes digital product design, strategy consulting, and immersive experiences, ensuring a robust support system for enterprises in various industries.

📋 Description

• 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

• 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

• 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.