Senior Data Scientist — Pricing & Commercial Analytics

CRG Search; Fort Mill (SC); On-site; USD 160,000 - 190,000; Full time

Job summary

CRG Search is seeking a Senior Data Scientist – Pricing & Commercial Analytics to build a dedicated pricing-focused data science capability. The role involves hands-on analytics, statistical modeling, and delivering data-driven recommendations that influence pricing across a large, complex portfolio.

You will collaborate with Pricing, Data Science, and Data Engineering teams to translate insights into actionable business outcomes and own investigations from hypothesis through implementation.

Qualifications

• 5+ years of experience in Data Science, Statistics, or Quant analytics.
• Experience translating findings into actionable business recommendations.
• Strong foundation in statistics and statistical modeling.

Responsibilities

• Analyze pricing and transactional data across 31,000 SKUs, markets, customers, and product categories to identify opportunities for improved rate performance.
• Investigate pricing patterns, seasonality, customer behavior, demand, and other factors that influence revenue and utilization.
• Develop statistical models to understand pricing impact on business performance.
• Evaluate pricing opportunities and determine appropriate methodologies for complex questions.
• Communicate findings clearly to Pricing and business stakeholders.

Skills

Python

SQL

Data analysis

Statistics

Communication

Education

Master's degree in a quantitative field

Tools

Spark

Databricks

Job description

A leading, multi-billion-dollar public company in the industrial services sector is seeking a Senior Data Scientist – Pricing & Commercial Analytics who will help build a dedicated pricing-focused data science capability.

This is a high-impact opportunity for a hands-on Data Scientist, Statistician, or quantitative professional who enjoys digging deeply into data, uncovering meaningful patterns, and translating statistical analysis into actionable business recommendations.

In this role, you will use advanced analytics and statistical modeling to uncover pricing opportunities across a large, complex commercial portfolio. You’ll investigate patterns across products, customers, markets, and business segments, working closely with Pricing, Data Science, and Data Engineering teams to solve ambiguous problems and develop insights that can directly influence business performance.

This role is best suited to someone who enjoys owning an ambiguous problem from initial question through analysis and recommendation, rather than simply executing predefined analytical requests.

Location: Fort Mill, SC| On-Site

Compensation: $160,000 - $190,000 + 10% bonus

Responsibilities

• Analyze pricing and transactional data across approximately 31,000 SKUs, markets, customers, and product categories to identify opportunities for improved rate performance
• Investigate pricing patterns, seasonality, customer behavior, demand, and other factors that influence revenue and utilization
• Develop statistical models and analytical approaches to understand the relationship between pricing and business performance
• Evaluate pricing opportunities and determine the appropriate statistical methodology to answer complex and ambiguous business questions
• Analyze price response and elasticity to help identify opportunities to improve pricing outcomes
• Develop data-driven pricing recommendations and clearly communicate findings to Pricing and other business stakeholders
• Partner with Data Engineering to obtain, structure, and prepare the datasets needed for analysis
• Collaborate with Data Science colleagues to develop predictive models and analytical solutions that can be implemented in production
• Refine analytical approaches as new data, market conditions, and business questions emerge
• Take ownership of investigations from the initial hypothesis through analysis, recommendation, and implementation
• Communicate complex statistical concepts and findings clearly to both technical and non-technical stakeholders

Qualifications:

• 5+ years of experience in Data Science, Statistics, Quantitative Analytics, or a related field
• Demonstrated experience independently investigating complex datasets and translating findings into actionable business recommendations
• Strong foundation in statistics and statistical modeling, with the ability to select and defend the appropriate analytical approach
• Strong proficiency in Python and SQL
• Experience working with transactional, customer, pricing, or other large-scale commercial datasets
• A curious, analytical mindset and the persistence to investigate a problem deeply rather than jumping to a quick conclusion
• Ability to work independently while collaborating effectively with Pricing, Data Science, Data Engineering, and other business stakeholders
• Strong communication skills and the ability to translate technical findings into clear business recommendations
• Commercial awareness and an interest in understanding how analytical insights can translate into measurable business results

Preferred Qualifications:

• Experience with pricing analytics, price elasticity, revenue optimization, demand modeling, or related commercial analytics
• Experience in retail, consumer, equipment rental, construction, logistics, or another data-rich commercial environment
• Experience with Spark and/or Databricks
• Experience developing predictive or machine learning models
• Exposure to production model implementation or model deployment
• Master's degree in Statistics, Data Science, Mathematics, Computer Science, Economics, or another quantitative discipline

Why This Opportunity?

This is an opportunity to apply data science to pricing decisions with significant financial impact and organizational visibility.

You’ll have the autonomy to investigate pricing questions, determine the appropriate analytical approach, and develop recommendations that can influence pricing across a large and complex portfolio.

The organization is also building out a dedicated pricing-focused data science capability, giving this individual an opportunity to help shape how advanced analytics and statistical modeling are applied to pricing over time.