THIS OPENING IS AVAILABLE FOR CANDIDATES IN LATIN AMERICA, NOT LIMITED TO ONLY MEXICO.
Sonatafy Technology , headquartered in Scottsdale, Arizona, is an award-winning nearshore software development company with a strong reputation. They have a dedicated in-house team of engineers, offering end-to-end software solutions and supporting client development staff augmentation. Catering to companies of all sizes and industries, including some of the world's largest brands, Sonatafy Technology is a trusted provider of nearshore enterprise-level cloud and mobile application software development services.
Responsibilities:
Analytics and Data Engineering
- Analyze large datasets to surface trends, patterns, and actionable business insights.
- Build and maintain data models, transformations, and pipelines using SQL and dbt.
- Collaborate with stakeholders to define metrics, KPIs, and reporting requirements.
- Support data governance, ensuring data quality, integrity, and accessibility across the organization.
- Document processes, workflows, and analysis outcomes for cross-functional teams.
- Work with U.S. government-related datasets and provide domain-specific insights (preferred experience).
Machine Learning and Predictive Modeling
- Design, build, and evaluate supervised and unsupervised ML models (classification, regression, clustering, forecasting).
- Lead problem framing conversations with stakeholders to translate business questions into ML-ready problem statements.
- Conduct feature engineering, selection, and transformation to prepare data for model training.
- Validate and communicate model performance using appropriate evaluation metrics (AUC, RMSE, F1, precision/recall, etc.).
- Support lightweight model deployment and monitoring, flagging performance drift and recommending retraining triggers.
- Contribute to experiment design and A/B testing frameworks where applicable.
Requirements and Skills:
- 5+ years of experience in Data Analytics, Data Science, or a combined analytics and ML role.
- Demonstrated experience building and deploying ML models in a business context, not just academic or exploratory work.
- Strong analytical and problem-solving mindset with the ability to translate complex data into clear, actionable insight.
- Excellent communication skills to work effectively with both technical and non-technical stakeholders.
Technical Skills:
- Data libraries: pandas, NumPy, matplotlib, seaborn
- ML libraries: scikit-learn, XGBoost, LightGBM, or equivalent
- Model evaluation and validation: cross-validation, train/test splits, hyperparameter tuning
- Strong SQL skills including querying, optimization, and data modeling.
- Experience with dbt for building and vers