Data Scientist, Pricing & Margin Optimization

RS Components; Fort Worth (TX); On-site; USD 120,000 - 170,000; Full time

Job summary

RS Group is modernizing sales quoting, pricing, and revenue processes by leveraging advanced analytics and data science. The Data Scientist will identify opportunities to optimize margins across customers, products, and channels and deliver data-driven insights to sales, pricing, and procurement teams.

You will build predictive models, apply machine learning, and enable self-service analytics while ensuring governance and documentation.

Qualifications

• Proficient in Python, SQL and ML methods.
• Experience turning complex models into business insights.
• Strong data engineering and feature-building skills.
• Ability to work with stakeholders and present narratives.
• Experience with Snowflake, Spark, AWS, ERP/SAP/Salesforce is a plus.
• Bachelor's degree in a technical field or equivalent experience.

Responsibilities

• Translate complex data into actionable recommendations for pricing, sales, and procurement.
• Develop predictive models for margin improvement.
• Analyze margin and growth across customers, products, suppliers, and channels.
• Identify margin leakage drivers such as discounting and cost fluctuations.
• Enable self-service analytics for business stakeholders.
• Maintain model documentation and data pipelines.
• Ensure data governance and compliance.

Skills

Python

SQL

Statistics

ML knowledge

Data engineering

Price theory

Stakeholder management

Problem solving

Ideation

Interpersonal skills

Education

Bachelor's degree in technical field

Tools

Snowflake

AWS

Spark/Databricks

ERP/SAP/Salesforce

PowerBI

Job description

RS Group is modernizing sales quoting, pricing, and revenue processes by leveraging advanced analytics and data science. The Data Scientist will identify opportunities to optimize margins across customers, products, and channels and deliver data-driven insights to sales, pricing, and procurement teams.

You will build predictive models, apply machine learning, and enable self-service analytics while ensuring governance and documentation.