Manager, Visa Consulting and Analytics (VCA), Intelligence & Data Solutions (IDS), Data Science

The IDS team is looking for a manager to lead, design, and implement high‑impact analytics, machine learning, and Generative AI solutions. This role combines technical leadership, hands-on data engineering, traditional statistical modeling, and cutting-edge AI development, including LLMs and agentic workflows. The ideal candidate is a versatile data scientist and engineer who can work from raw data all the way to production-grade solutions, building models, developing automation pipelines, and leveraging Generative AI to transform how VCA delivers insights to clients in Latin America. Responsibilities: Drive (hands-on) the end‑to‑end lifecycle of analytical, machine learning, and Generative AI projects—from business problem definition to model development, validation, deployment, and monitoring. Perform (hands-on) advanced data wrangling, feature engineering, and dataset creation using complex, large‑scale, and unstructured data sources (Hadoop, PySpark, Presto, SQL, Hive). Build and deploy traditional ML and statistical models (Linear & Logistic Regression, Decision Trees, Random Forests, K-Nearest Neighbors, K-Means Clustering, LLM, XGBoost, Neural Networks, …). Develop and implement Generative AI solutions, including LLM‑based pipelines, retrieval‑augmented generation (RAG), prompt engineering, and AI agents for automation and decision support. Collaborate with engineering teams to design scalable solutions that integrate both ML and GenAI components into production environments. Create frameworks and reusable components to accelerate internal model development and improve team efficiency. Translate complex analytical concepts into actionable recommendations for technical and non‑technical stakeholders. Mentor junior data scientists, fostering excellence in analytical methods, coding best practices, and emerging AI techniques. Promote the adoption of Generative AI across the organization, identifying opportunities for automation, knowledge enhancement, and operational efficiency. Build strong client relationships, supporting scoping discussions, requirement gathering, roadmap development, and solution delivery. This is a hybrid position. Expectation of days in the office will be confirmed by your Hiring Manager.  Basic Qualifications: 5+ years of relevant work experience with a Bachelor’s Degree or at least 2 years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD) or 0 years of work experience with a PhD, OR 8+ years of relevant work experience. Preferred Qualifications: 7+ years of relevant work experience in developing machine learning models with a Bachelor's degree, OR 4+ years with an Advanced Degree (Master or PhD). Post-graduate degree in a quantitative field such as Statistics, Mathematics, Data Science, Computer Science, Informatics, Economics, or Engineering (Master or PhD). Minimum of 5+ years of hands-on expertise in applying and deploying Machine Learning solutions to solve business problems, with proven experience in the complete model lifecycle (development, validation, and production deployment). Deep theoretical and practical knowledge of machine learning techniques, including but not limited to Linear/Logistic Regression, Decision Trees (Random Forests, XGBoost), Clustering, and Neural Network. Strong programming proficiency in Python and its data science ecosystem (e.g., Pandas, Scikit-learn, NumPy, PySpark) for building and implementing ML models. Proven ability to perform data manipulation and feature engineering on large, complex datasets using distributed computing platforms (e.g., Hadoop, PySpark) and database systems (SQL, Hive, Python). Experience in presenting complex analytical results and ideas to stakeholders and tailoring communication to various audience levels. Hands on experience with Generative AI, including LLMs, fine tuning, prompt engineering, RAG, and creation of AI agents. Experience l ... (truncated, view full listing at source)