Senior Data Scientist — ML, LLMs & MLOps Lead

ManpowerGroup Global, Inc.; Philadelphia (Philadelphia County); On-site; USD 140,000 - 180,000; Full time

Benefits offered by this job

Medical Plan

Dental Plan

Vision Plan

Health Savings Account

401(k) with Match

Weekly Pay

Job summary

ManpowerGroup Global, Inc. seeks a Senior Data Scientist in Philadelphia, onsite, to lead ML model development and deployment for digital transformation.

You will collaborate with cross‑functional teams to build scalable data pipelines, apply deep learning and MLOps, and implement LLMs for automation and personalization. The role requires 7–10 years in data science, strong Python/SQL, cloud experience (GCP/AWS), and expertise with knowledge graphs (Neo4j) and modern ML frameworks.

Qualifications

• 7–10 years of experience in Data Science, ML, or related fields.
• Strong expertise in Python, SQL and ML frameworks (TensorFlow, PyTorch, Scikit-Learn).
• Experience with MLOps tools (MLflow, Kubeflow, Airflow) for deployment/monitoring.
• Proficiency in cloud platforms (GCP, AWS) and scalable data engineering.
• Hands-on experience with Knowledge Graphs (Neo4j) and LLMs (GPT, BERT, LLaMA).

Responsibilities

• Lead development and deployment of advanced ML models to support decisions.
• Collaborate with cross-functional teams to design scalable data pipelines and AI solutions.
• Apply deep learning, neural networks and MLOps to optimize performance and reliability.
• Implement and tune LLMs and Generative AI for automation and engagement.
• Work with knowledge graphs to enhance recommendations and personalization.

Skills

Python

SQL

Deep Learning

MLOps

Cloud Platforms

Knowledge Graphs

LLMs / Generative AI

Neo4j

Tools

MLflow

Kubeflow

Airflow

Job description

ManpowerGroup Global, Inc. seeks a Senior Data Scientist in Philadelphia, onsite, to lead ML model development and deployment for digital transformation.

You will collaborate with cross‑functional teams to build scalable data pipelines, apply deep learning and MLOps, and implement LLMs for automation and personalization. The role requires 7–10 years in data science, strong Python/SQL, cloud experience (GCP/AWS), and expertise with knowledge graphs (Neo4j) and modern ML frameworks.