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

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.

Originally posted on Himalayas

Responsibilities:

Exploratory Data Analysis (EDA):

Data Wrangling and Preparation:

Machine Learning Modeling:

Data Visualization:

Python Data Stack:

Model Explainability:

Collaboration and Communication:

Requirements for this challenge:

Expected Certifications

Our benefits include:

[Job-29268] Data & Analytics Engineer, Colombia at CI&T