Role Overview

We’re hiring a mid-to-senior Machine Learning Engineer / Data Scientist to build and deploy machine learning solutions that drive measurable business impact. You’ll work across the ML lifecycle—from problem framing and data exploration to model development, evaluation, deployment, and monitoring—often in partnership with client stakeholders and internal delivery teams.

You should be strong in core data science and applied machine learning, comfortable working with real-world data, and capable of turning modeling work into production‑ready systems.

Key Responsibilities
- Problem Framing & Stakeholder Partnership
- Translate business questions into ML problem statements (classification, regression, time series forecasting, clustering, anomaly detection, recommendation, etc.)
- Collaborate with stakeholders to define success metrics, evaluation plans, and practical constraints (latency, interpretability, cost, data availability)
- Data Analysis & Feature Engineering
- Use SQL and Python to extract, join,



and analyze data from relational databases and data warehouses
- Perform data profiling, missingness analysis, leakage checks, and exploratory analysis to guide modeling choices
- Build robust feature pipelines (aggregation, encoding, scaling, embeddings where appropriate) and document assumptions
- Model Development (Core ML)
- Train and tune supervised learning models for tabular data (e.g., logistic/linear models, tree-based methods, gradient boosting such as XGBoost/LightGBM/CatBoost, and neural nets for structured data)
- Apply strong tabular modeling practices: handling missing data, categorical encoding, leakage prevention, class imbalance strategies, calibration, and robust cross-validation
- Build time series models (statistical and ML/DL approaches) and validate with proper backtesting
- Apply clustering and segmentation techniques (k-means, hierarchical, DBSCAN, Gaussian mixtures) and evaluate stability and usefulness
- Apply statistics in p

📌 Machine Learning Engineer (Bogotá)
🏢 Fusemachines
📍 Bogotá