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Data Scientist - CRM Intelligence AI Orchestration

Galent · New York, United States

Spotted 1h ago

Job details

Work mode
Hybrid
Posted
Oct 14, 2026
Last confirmed open
Oct 14, 2026
Job description

About this role

Job Title: Data Scientist - CRM Intelligence AI Orchestration Location: New York, NY (Hybrid) Job Summary Seeking a Data Scientist with strong expertise in CRM Analytics, Machine Learning, Generative AI, AI Orchestration, and Customer Intelligence. The role focuses on leveraging CRM data and AI-driven solutions to improve customer engagement, operational efficiency, intelligent automation, and customer experience.

Key Responsibilities

  • Analyze CRM data from platforms such as Salesforce, Microsoft Dynamics 365, Oracle CX, SAP CRM, or similar enterprise customer platforms.
  • Assess CRM data landscapes and identify opportunities for AI-driven transformation, automation, and customer experience improvement.
  • Design and implement AI orchestration solutions involving AI services, enterprise applications, knowledge repositories, and business workflows.

Customer Segmentation

Lead Scoring Opportunity Prediction Churn Prediction Next Best Action Customer Lifetime Value (CLV) Build and deploy Generative AI solutions utilizing Large Language Models (LLMs), Prompt Engineering, Retrieval-Augmented Generation (RAG), and AI-powered enterprise search. Integrate CRM platforms with enterprise knowledge sources, document repositories, workflow systems, and conversational AI solutions.

Work with structured and unstructured customer data, including emails, chat transcripts, service tickets, call summaries, and CRM interactions. Translate business requirements into AI and analytics solutions that improve customer engagement, productivity, and operational efficiency. Implement Responsible AI practices, including governance, explainability, security, privacy, and compliance controls.

Collaborate with business, architecture, CRM, and engineering teams to deliver scalable AI solutions. Required Skills Strong experience in Data Science, Machine Learning, and Advanced Analytics with a focus on Customer, Sales, Service, and CRM domains. Hands-on experience with CRM analytics and customer intelligence modeling.

Experience with Generative AI, LLMs, Prompt Engineering, RAG, and AI-powered search. Experience designing and implementing AI orchestration solutions.

Strong understanding of Agentic AI concepts, including

Autonomous Agents Task Planning Tool Usage Memory Management Human-in-the-Loop Architectures Proficiency in: Python SQL Pandas Scikit-Learn TensorFlow PyTorch LangChain Semantic Kernel AutoGen CrewAI or similar AI frameworks Experience with cloud AI and analytics platforms such as: Azure AI Azure Machine Learning Databricks Snowflake AWS SageMaker Equivalent cloud platforms Mandatory Skill: Python - Data Science Preferred Skills Experience with CRM modernization or digital transformation initiatives.

Experience with Vector Databases, Knowledge Graphs, and GraphRAG architectures. Experience with MLOps, CI/CD, Model Monitoring, and AI Operations. Knowledge of Customer Service AI Copilot solutions, Conversational AI, and AI Agent platforms.

Good-to-have skills

  • MLOps - Python MySQL Power BI Tableau Qualifications Excellent analytical thinking and problem-solving capabilities.
  • Strong communication skills and the ability to present insights through data storytelling.
  • Ability to influence business stakeholders and present AI recommendations to executive leadership.
  • Strong collaboration skills across business, architecture, CRM, and engineering teams.
  • We are an Equal Opportunity Employer.
  • All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, citizenship status, age, disability, genetic information, protected veteran status, or any other characteristic protected by applicable law. https://www.e-verify.gov/sites/default/files/everify/posters/IER_RighttoWorkPoster.pdf
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