Data Scientist II performing analytics and modeling to improve fraud strategies at Truist. Engaging with stakeholders and developing data - driven solutions for risk management and business outcomes.
About the role
- Director of Data Science leading personalization, recommendation systems, and GenAI chatbot development at Gartner. Managing teams and strategic AI initiatives for enhanced client experiences.
Responsibilities
- Lead the data science roadmap spanning personalization, recommendation systems, and GenAI chatbot development
- Architect AI-powered chatbot systems including intelligent search, recommendation engines, context-aware retrieval, and Model Context Protocol (MCP) servers
- Apply transformer-based models, LLMs, and advanced techniques to enhance recommendation relevance
- Leverage internal and external data to model client company priorities
- Collaborate with engineering, product, UX, and business leaders to prioritize ideas and launch MVPs
- Lead a team of data scientists, driving enhancements in accuracy, coverage, latency, scalability, stability, and adoption
- Stay current on fast-moving AI/ML advancements
Requirements
- 8-12 years of experience in data science, machine learning, or AI
- At least 3 years managing data science and engineering teams
- Master’s Degree or PhD in a quantitative field (math, computer science, engineering, etc.) required
- Proven leadership developing personalization systems, recommendation engines, search/ranking solutions, conversational AI, chatbots, and GenAI applications powered by transformer-based models and LLMs
- Strong communication skills to influence executives
- Deep expertise in ML lifecycle, Lean product principles, MLOps, experimentation frameworks, and production recommender/GenAI systems
- Proficiency with Python, ML frameworks (scikit-learn, NLTK, PyTorch, TensorFlow, Hugging Face, LangChain), SQL/relational databases (Oracle), NoSQL/graph databases (MongoDB), vector databases (Pinecone, Weaviate), distributed ML (Spark), Linux/shell scripting, and cloud platforms (AWS SageMaker, Azure ML).
Benefits
- Competitive salary
- Generous paid time off policy
- Charity match program
- Group Medical Insurance
- Parental Leave
- Employee Assistance Program (EAP)
- Professional development and unlimited growth opportunities
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