The Data Science Lead is a pivotal technical leader responsible for architecting and deploying production-grade Machine Learning (ML) and Artificial Intelligence (AI) solutions. You will steer the development of sophisticated predictive models within a robust CI/CD/CT (Continuous Training) framework. Leveraging the Azure ecosystem (Databricks, Spark, Azure ML), you will transform big raw data into scalable intelligence, ensuring that models are not just "notebook experiments" but resilient enterprise assets.

Responsibilities

Architectural Leadership: Lead the design and delivery of end-to-end ML systems, prioritizing MLOps principles to ensure model reproducibility, auditability, and scalability.

Full-Lifecycle Development: Oversee the journey from hypothesis and Exploratory Data Analysis (EDA) to feature engineering, model selection, and production deployment.

Cross-Functional Synergy: Act as the technical bridge between Data Engineers (for ETL/Feature Store optimization) and Business Stakeholders (to translate KPIs into objective functions).

Infrastructure Automation:



Architect automated pipelines for data validation, model profiling, and hyperparameter tuning using Azure Machine Learning Services.

Governance & Monitoring: Establish rigorous monitoring for Data Drift and Concept Drift, ensuring model performance remains optimal post-deployment.

Requirements

Experience: 5–8 years of total experience, with 4+ years specifically in a hands- on Data Science role and 2+ years leading technical teams or complex projects.

Education: BE/BS or MS/PhD in Computer Science, Statistics, Mathematics, Physics, or a related quantitative field.

1. Advanced Modeling & Mathematics- Deep Learning & Classical ML: Proficiency in supervised/unsupervised learning, including Gradient Boosted Trees (XGBoost/LightGBM), Random Forests, and Neural Networks.

Statistical Rigor: Mastery of hypothesis testing, Bayesian inference, and error analysis. Ability to design complex experiment

📌 Data Science Lead (Perú)
🏢 Resilient
📍 Perú