Lead Data Scientist

Lead Data Scientist role focused on creating and deploying ML/AI solutions for marketing and business engagement within a regulated enterprise environment. Responsibilities include technical leadership, model development, platform integration, and team management, with a strong emphasis on production stability and compliance.

What you'd actually do

  1. Lead the solution and a team of data scientists delivering AI and ML solution for marketing and business engagement use cases
  2. Accountability for technical decisions, project outcomes, timelines, and production stability within a defined domain
  3. Lead the planning and execution of data science use cases, ensuring alignment with business goals and objectives
  4. Design, train, and optimize machine learning and deep learning models for a variety of marketing and business engagement use cases
  5. Analyze complex data sets to identify trends, patterns, and actionable insights that can inform business strategies

Skills

Required

  • Bachelor's or master's degree in computer science, Data Science, Engineering, Mathematics, or a related field
  • 8+ years of overall experience in AI/ML engineering and/or data science
  • 5+ years of insurance business and/or financial industry experience with sales, marketing, and/or customer engagement analytics
  • Proven experience designing, deploying, and operating production ML and / or GenAI solutions, including APIs, batch, and real-time inference
  • Experience in developing Machine Learning models using Python (preferably in the cloud)
  • Familiarity with best practices for responsible AI, including data privacy, bias mitigation, and/or model monitoring
  • Strong SQL knowledge and data analysis skills for data anomaly detection and Exploratory Data Analysis
  • Experience with Dominos, Power BI, and/or Azure ML
  • Statistical Knowledge: A strong understanding of statistics and mathematics is essential for data analysis and prediction
  • Use predictive modeling or AI solutions to increase and optimize customer experience/communication, revenue generation, ad targeting, and other business outcomes
  • Very good presentation skills to present results clearly and effectively by creating presentations with storytelling, visualizations & results
  • Very good problem solver and excellent communication skills - both written and verbal

Nice to have

  • Experience with employee benefits plans is a plus
  • Hands-on experience with cloud platforms (Azure/Databricks)
  • Hands-on expertise with Retrieval-Augmented Generation (RAG) architectures, including integrating external data sources and vector databases to enhance LLM outputs
  • Strong understanding of prompt engineering, fine-tuning, and evaluation of generative models for real-world applications
  • Ability to build, optimize, and scale GenAI pipelines for tasks such as document Q&A, summarization, chatbots, and knowledge retrieval

What the JD emphasized

  • production ML and / or GenAI solutions
  • production stability
  • regulated, enterprise environment
  • responsible AI

Other signals

  • Lead the solution and a team of data scientists delivering AI and ML solution for marketing and business engagement use cases
  • Accountability for technical decisions, project outcomes, timelines, and production stability within a defined domain
  • Design, train, and optimize machine learning and deep learning models for a variety of marketing and business engagement use cases
  • Proven experience designing, deploying, and operating production ML and / or GenAI solutions, including APIs, batch, and real-time inference
  • Experience with Dominos, Power BI, and/or Azure ML