Sr. Manager - Data Science

Job Description

Role Overview:You will be part of the Client Services Data & AI Solutions Team at Visa, where you will play a crucial role in building an open and trusted data and AI culture. Your main responsibility will be to lead the development and integration of AI technologies into the Client Services operations. Your focus will be on leveraging generative AI, MLOps, AI model fine-tuning, and enrichment pipelines to enhance service delivery and predictive capabilities.Key Responsibilities:- Establish data and AI processes and automation aligned with business and technology requirements, utilizing supported data platforms, MLOps tooling, and models.- Build production-grade AI services such as LLM-based applications, RAG pipelines, recommendation systems, forecasting, and classification.- Develop and maintain data models and schemas optimized for analytics, ML feature stores, and AI workloads.- Deliver end-to-end data engineering and AI projects including ingestion, modeling, pipeline development, feature engineering, model training, deployment, and monitoring.- Enforce best practices in data architecture and governance, provide expertise in data modeling, and MLOps.- Collaborate with cross-functional teams to translate requirements into data and AI solutions.- Implement data validation, quality checks, and model evaluation at each stage.- Apply Agile principles to plan, build, test, and iterate data & AI solutions, and document architecture, dictionaries, and models.- Communicate complex data and AI concepts clearly to technical and non-technical audiences.- Stay updated on trends in cloud engineering, distributed computing, LLMs, models, databases, orchestration, etc.Qualifications:Basic Qualifications:- 8 years of work experience with a Bachelors Degree in the STEM or related field, or 6 years of experience with an Advanced degree (Masters), or 1 years of experience with a PhD.Preferred Qualifications:- 8-12 years of experience in AI, Data Science, Data Modeling, and machine learning solutions.- Hands-on experience using LLM ecosystems like OpenAI, Azure OpenAI, Vertex AI, fine-tuning LLMs, and using advanced AI techniques like RAG.- Deep knowledge of data warehousing, ETL/ELT, data modeling, and data architecture.- Experience designing feature stores and ML-ready datasets.- Expertise in SQL, Python, and relational databases.- Proven experience with large datasets using Hadoop (Hive), Spark, Python (pandas, NumPy), Presto, and SQL.- Experience with Python ML/AI frameworks like scikit-learn, PyTorch, TensorFlow.- Experience in the core machine learning workflow, including data handling, cleaning, wrangling, feature engineering, and modeling with algorithms like Linear Regression, Decision Trees, and XGBoost.- Experience with orchestration and scheduling tools such as Airflow.- Understanding of visualization tools like Tableau, QlikView, Power BI.- Nice to have experience with cloud data platforms and pipeline management in AWS, GCP, Azure.- Strong problem-solving skills, analytical skills, and attention to detail.- Effective communicator of statuses, issues, and risks.- Team player and collaborator, comfortable in a matrixed environment and with cross-functional delivery. Role Overview:You will be part of the Client Services Data & AI Solutions Team at Visa, where you will play a crucial role in building an open and trusted data and AI culture. Your main responsibility will be to lead the development and integration of AI technologies into the Client Services operations. Your focus will be on leveraging generative AI, MLOps, AI model fine-tuning, and enrichment pipelines to enhance service delivery and predictive capabilities.Key Responsibilities:- Establish data and AI processes and automation aligned with business and technology requirements, utilizing supported data platforms, MLOps tooling, and models.- Build production-grade AI services such as LLM-based applications, RAG pipelines, recommendation systems, forecasting, and classification.- Develop and maintain data models and schemas optimized for analytics, ML feature stores, and AI workloads.- Deliver end-to-end data engineering and AI projects including ingestion, modeling, pipeline development, feature engineering, model training, deployment, and monitoring.- Enforce best practices in data architecture and governance, provide expertise in data modeling, and MLOps.- Collaborate with cross-functional teams to translate requirements into data and AI solutions.- Implement data validation, quality checks, and model evaluation at each stage.- Apply Agile principles to plan, build, test, and iterate data & AI solutions, and document architecture, dictionaries, and models.- Communicate complex data and AI concepts clearly to technical and non-technical audiences.- Stay updated on trends in cloud engineering, distributed computing, LLMs, models, databases, orchestration, etc.Qualifications:Basic Qualifications:- 8

Keyskills :
Data ScienceData ModelingMachine LearningData warehousingData architectureSQLPythonRelational databasesHadoopSparkNumPyPrestoLinear RegressionDecision TreesAirflowTableauQlikViewPower BIAWSGCPAzureLLM ecosystemsRAGETLELTPandas