Hybrid Senior AI & Data Scientist: Sales AI & MLOps

Hewlett Packard Enterprise Development LP; Westford (MA); Hybrid; USD 120,000 - 228,000; Full time

Benefits offered by this job

Health benefits

Career development

Inclusive culture

Job summary

Hewlett Packard Enterprise Development LP is seeking a Senior AI & Data Scientist to design, deploy, and scale AI/ML solutions across sales and operations. The role emphasizes building AI copilots, RAG systems, and data-driven insights from CRM and market data.

You will partner with Sales, Operations, and IT to prioritize high-value use cases, develop production-grade models, and monitor performance while staying current on AI innovations.

Qualifications

• Master degree in Data Science or related field with 7+ years' experience.
• Strong Python/SQL and ML frameworks (PyTorch, TensorFlow, Scikit-learn).
• Experience with Large Language Models (LLMs), prompt engineering, Retrieval-Augmented Generation (RAG).
• Experience with Salesforce or similar CRM platforms, cloud environments, and analytics tools.

Responsibilities

• Design, develop, and deploy AI/ML solutions that drive sales performance and operational efficiency.
• Build AI-powered copilots, intelligent assistants, and RAG solutions to improve seller productivity.
• Analyze CRM, sales, customer, and operations data to identify trends and opportunities.
• Develop dashboards and production-ready ML models with monitoring and governance.

Skills

Python

SQL

LLMs

RAG

MLOps

Sales analytics

Education

Master degree in Data Science / Computer Science / AI / Statistics

Tools

PyTorch

TensorFlow

Scikit-learn

Power BI

Tableau

Salesforce CRM

Azure Cloud

MLflow / MLOps

Job description

Hewlett Packard Enterprise Development LP is seeking a Senior AI & Data Scientist to design, deploy, and scale AI/ML solutions across sales and operations. The role emphasizes building AI copilots, RAG systems, and data-driven insights from CRM and market data.

You will partner with Sales, Operations, and IT to prioritize high-value use cases, develop production-grade models, and monitor performance while staying current on AI innovations.