Pricing & Revenue Optimization Data Scientist

DHL Regional Services, Inc.; Plantation (FL); On-site; USD 110,000 - 170,000; Full time

Job summary

DHL Regional Services, Inc. is seeking a Data Scientist for Pricing & Revenue Optimization to drive profitable growth through advanced analytics and experimentation.

You will build WTP models, optimize revenue and margins across customer segments, and support pricing decisions with rigorous data-driven insights. Responsibilities include deploying ML models, running pricing experiments (A/B and elasticity tests), and collaborating with Sales, Finance, Operations and IT to translate analytics into

Qualifications

• Proven ability to deploy predictive models in production.
• Strong background in pricing/revenue management.
• Experience with commercial or pricing teams is desirable.
• Experience in customer segmentation and behavioral analytics.

Responsibilities

• Develop and deploy willingness-to-pay models using machine learning.
• Design optimization models to balance volume growth and margin.
• Develop predictive churn and retention models.
• Design pricing experiments (A/B testing, elasticity testing).
• Collaborate with IT and data engineering to deploy models to production.
• Translate insights to cross-functional actions with Sales, Finance, Ops and Marketing.

Skills

Python

R

SQL

Pandas/NumPy/scikit-learn

Machine learning

Optimization

Time-series forecasting

A/B testing

Elasticity modeling

Big data tools (Spark)

Cloud environments

Pricing strategy

Education

Bachelor’s degree in Data Science, Statistics, Economics, Engineering, Mathematics, or related field

Tools

Spark

Cloud platforms (AWS/GCP)

Job description

DHL Regional Services, Inc. is seeking a Data Scientist for Pricing & Revenue Optimization to drive profitable growth through advanced analytics and experimentation.

You will build WTP models, optimize revenue and margins across customer segments, and support pricing decisions with rigorous data-driven insights. Responsibilities include deploying ML models, running pricing experiments (A/B and elasticity tests), and collaborating with Sales, Finance, Operations and IT to translate analytics into