Senior Manager, Data Science

Visa Visa · Fintech · Austin, TX

Senior Manager, Data Science role at Visa focused on leading the development and implementation of AI and ML models, particularly for the Post Purchase Platform. The role involves managing production ML/Gen AI products, developing strategies for data wrangling and model retraining, ensuring data quality, and advising on technical specifications. It emphasizes transforming digital offerings by leveraging AI for current products and developing new ones for banking and fintech partners, with a focus on fraud detection models.

What you'd actually do

  1. Implements, monitors and maintains a suite of production machine learning, NLP models and Gen AI products that adhere to data science and machine learning standards.
  2. Develops strategies and tools to drive efficiencies across data extraction, frequent retuning of models and ensure data quality and completeness using data wrangling, LLMs and artificial intelligence.
  3. Ensures adherence to Visa’s model review management processes, data management principles, governance, process, and tools to maintain data quality across products.
  4. Advises on technical specifications during discussions with collaborators (e.g., model review management team, software development team, product team, clients) to identify and clarify sophisticated technical or business requirements and identify business needs and upstream and/or downstream system/application dependencies.
  5. Identifies complex trends across relevant data sources and uses insights to plan platform-wide future solution updates.

Skills

Required

  • Python
  • SQL
  • Machine Learning
  • NLP
  • Gen AI
  • Data Wrangling
  • Data Quality
  • Model Review Management
  • Data Management
  • Governance
  • Dashboards
  • Tableau
  • Power BI

Nice to have

  • XGBoost
  • Neural Network models
  • LLMs for feature extraction
  • Agentic workflows
  • Payments experience
  • Building high volume transaction and data processing systems

What the JD emphasized

  • production machine learning, NLP models and Gen AI products
  • frequent retuning of models
  • building/fine tuning ML/AI models around fraud detection
  • building agentic workflows

Other signals

  • AI transformation journey
  • AI technologies have the potential to radically transform
  • implementing, monitoring and maintaining a suite of production machine learning, NLP models and Gen AI products
  • develops strategies and tools to drive efficiencies across data extraction, frequent retuning of models and ensure data quality and completeness using data wrangling, LLMs and artificial intelligence
  • building/fine tuning ML/AI models around fraud detection