Pricing Data Scientist - ML-Driven Revenue Growth

Radwell International; Downers Grove (IL); On-site; USD 80,000 - 105,000; Full time

Benefits offered by this job

Health, dental, and vision coverage

Short-term and long-term disability

Life insurance $50,000

401(k) plan with 3% employer match

Paid holidays and 15 days PTO

Job summary

Radwell International in Downers Grove, IL is seeking a Pricing Analyst to design data-driven pricing strategies, build in-house price optimization engines, and align pricing with revenue goals. You will analyze large datasets, forecast demand elasticity, and collaborate with Marketing, Product, and Finance.

The ideal candidate has a degree in Economics/Statistics/Data Science and 1+ years in pricing or analytics, with proficiency in SQL, Python, R, and Excel.

Qualifications

• Bachelor's degree in Economics, Statistics, Mathematics, Data Science, Business, or related field.
• 1+ years of experience in analytics, pricing science, revenue management, or similar.
• Experience with pricing models, optimization techniques, and demand forecasting.
• Familiarity with machine learning, regression models, and pricing analytics.

Responsibilities

• Design and implement data-driven pricing strategies aligned with revenue goals.
• Build in-house price optimization engine using ML and optimization techniques.
• Monitor competitor pricing, market trends, and benchmarks.
• Collaborate with Marketing, Product, and Finance to align pricing with objectives.
• Prepare pricing analyses, insights, and recommendations for senior management.
• Stay current with data science and pricing methodologies.

Skills

SQL

Python

R

Excel

Pricing strategies

Elasticity

Competitive analysis

Communication skills

Data interpretation

Education

Bachelor's degree in Economics, Statistics, Mathematics, Data Science, Business

Master's or Ph.D. is a plus

Tools

SQL

Python

R

Excel

Job description

Radwell International in Downers Grove, IL is seeking a Pricing Analyst to design data-driven pricing strategies, build in-house price optimization engines, and align pricing with revenue goals. You will analyze large datasets, forecast demand elasticity, and collaborate with Marketing, Product, and Finance.

The ideal candidate has a degree in Economics/Statistics/Data Science and 1+ years in pricing or analytics, with proficiency in SQL, Python, R, and Excel.