Data Scientist - Enterprise Analytics & ML Pipelines

Manpower, Inc.; Greenville (SC); On-site; USD 59,000 - 84,000; Full time

Benefits offered by this job

Competitive pay

Medical, Dental, Vision, and 401(k)

Life, Disability, Travel Insurance

Weekly pay via direct deposit

Career growth and training

Job summary

Manpower, Inc. seeks a Data & Analytics (D&A) Developer II / Data Scientist for a global energy technology client in Greenville, SC.

You will analyze large datasets, develop machine learning and forecasting models, and build Python-based data pipelines to support operations and strategic decisions. Collaborate with Data Engineers, Program Managers, Operations, and Digital teams to translate complex findings into actionable insights.

Qualifications

• Experience analyzing large structured and unstructured enterprise datasets.
• Ability to build and validate ML, forecasting, predictive, and scenario-planning models.

Responsibilities

• Analyze large structured and unstructured datasets from enterprise systems to identify patterns and actionable insights.
• Develop and validate machine learning, forecasting, predictive, and scenario-planning models for operational and strategic decisions.
• Build and maintain Python-based data pipelines for ETL, model training, and analytical workflows.
• Perform scenario and variance analysis to compare planning assumptions against actual project execution.
• Partner with Data Engineers, Program Managers, Operations, and stakeholders to translate challenges into scalable data science solutions.

Skills

Data analysis

Python for data science

SQL

ML/forecasting

Data pipelines

Collaboration

Tools

Python

SQL

pandas

scikit-learn

NumPy

SciPy

Job description

Manpower, Inc. seeks a Data & Analytics (D&A) Developer II / Data Scientist for a global energy technology client in Greenville, SC.

You will analyze large datasets, develop machine learning and forecasting models, and build Python-based data pipelines to support operations and strategic decisions. Collaborate with Data Engineers, Program Managers, Operations, and Digital teams to translate complex findings into actionable insights.