US E Es - Lead Data Scientist Genai, Financial Planning & Analysis - Strategic Analytics

Lead Data Scientist GenAI role focused on developing and deploying generative AI solutions for financial planning and analysis within an enterprise setting. The role involves building data pipelines, APIs, and model deployment workflows, and partnering with business stakeholders to translate requirements into actionable insights and production-ready products.

What you'd actually do

  1. Designing, developing, and deploying artificial intelligence, machine learning, and advanced analytics solutions for business stakeholders
  2. Building and maintaining scalable data pipelines, application programming interfaces, and model deployment workflows in cloud environments
  3. Partnering with finance, strategy, and operational teams to translate business requirements into technical solutions and actionable insights
  4. Supporting the development of generative artificial intelligence use cases, prototypes, and production-ready products aligned to strategic priorities
  5. Monitoring solution performance, maintaining technical documentation, and identifying opportunities to improve reliability, efficiency, and adoption

Skills

Required

  • 4+ years of experience in data science, machine learning engineering, data engineering, or software engineering
  • 3+ years of experience developing solutions using Python
  • 2+ years of experience working with cloud platforms such as Amazon Web Services, Microsoft Azure, or Google Cloud Platform
  • 2+ years of experience using Structured Query Language and working with relational or distributed data platforms
  • Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, Finance, or a related field

Nice to have

  • Master’s degree in Computer Science, Data Science, Engineering, Statistics, or a related field
  • Experience developing generative artificial intelligence or large language model solutions
  • Experience with machine learning operations tooling and model deployment frameworks
  • Experience building application programming interfaces or production data products
  • Experience supporting finance, financial planning and analysis, or enterprise strategy use cases
  • Experience with data visualization tools such as Tableau or Power BI

What the JD emphasized

  • generative artificial intelligence
  • production-ready products

Other signals

  • developing generative artificial intelligence use cases, prototypes, and production-ready products
  • partnering with finance, strategy, and operational teams to translate business requirements into technical solutions
  • building and maintaining scalable data pipelines, application programming interfaces, and model deployment workflows