Loading...
SeniorFull-timeMachine LearningAIMLData
Salary Range
$59,670 - $80,730 /year
This salary is estimated based on similar roles. The actual salary may vary.
As a Senior Data Scientist, you will contribute to the design and hands on delivery of advanced analytics and machine learning solutions that power Visa products and services. You will execute end to end analytics tasks spanning problem definition, data preparation, modeling, validation, and performance assessment while collaborating closely with senior data scientists and technical leads. You will help prototype and validate Generative AI and LLM based use cases, applying appropriate techniques aligned with business value, data constraints, and governance requirements.
Responsibilities:
• Contribute to technical design and implementation of advanced analytics and machine learning projects under guidance from senior and lead team members
• Execute end to end analytics workflows including problem framing, data exploration, feature engineering, model development, validation, and performance monitoring
• Write clean, well documented code and participate in peer reviews for notebooks, pipelines, and models to ensure quality and reproducibility
• Translate business questions into clear analytical approaches and scalable solutions, partnering with product and business stakeholders
• Support project scoping and methodology. Assist in drafting analytics scopes, delivery plans, and documentation for small to medium projects
• Prototype and validate Generative AI and LLM use cases including prompt engineering, retrieval augmented generation, and evaluation frameworks. Contribute to productionizing successful prototypes
• Select and apply appropriate ML and Generative AI techniques considering data availability, governance, privacy, security, and business objectives
• Ensure analytical outputs meet standards for quality, documentation, timelines, and budget constraints established by the project lead
• Contribute to continuous improvement by sharing best practices, new tools and methodologies, and reusable assets across the team
• Collaborate cross functionally with data engineering, product, platform, and risk teams to integrate solutions into production environmentsThis is a hybrid position. Expectation of days in the office will be confirmed by your Hiring Manager. 
