Staff Data Scientist- Pricing Science

About the role

The Staff Data Scientist- Pricing Science at Cscgeneration 2 will own the development and execution of advanced pricing science initiatives across the portfolio. You will establish rigorous experimentation frameworks to test pricing hypotheses and validate incremental impact before full rollout. This role requires synthesizing complex analytical findings into clear narratives that guide strategic merchandising choices. You will act as the primary analytical partner for finance and merchandising teams, aligning models with financial guardrails and brand objectives. The position involves translating volatile market signals into stable pricing rules that protect margin and volume. You will mentor junior analysts on best practices for causal identification and data quality standards. Day to day you will balance rapid experimentation cycles with the need for robust statistical evidence. Ultimately your work will shape the price architecture that drives revenue and profitability for multiple brands.

Key facts

What you'll do

• You will architect measurement frameworks that isolate causal effects of price changes on demand and assortment performance.
• You will build predictive models that forecast price elasticity at scale while controlling for seasonality and promotional interference.
• You will coordinate with merchandising leadership to translate assortment strategies into quantifiable pricing guardrails.
• You will design and analyze A/B tests that isolate price effects in highly competitive retail environments.
• You will construct pricing analytics dashboards that provide real time visibility into margin trade offs and performance outliers.
• You will synthesize cross functional insights from finance operations and merchandising to refine pricing hypotheses.
• You will lead the lifecycle of pricing experiments from hypothesis generation through rollout and post analysis review.
• You will develop scenario models that simulate the impact of promotional mixes and discount depth on overall contribution.
• You will establish data quality checks to ensure pricing models rely on clean and consistent transaction signals.
• You will communicate analytical roadmaps and trade offs to non technical stakeholders through concise presentations.
• You will partner with finance to align pricing guardrails with overall margin targets and risk appetite.
• You will evaluate vendor tools and open source libraries to enhance pricing modeling capabilities.
• You will document methodologies and assumptions to ensure reproducibility and regulatory clarity.
• You will identify opportunities to standardize pricing metrics across brands to enable portfolio level insights.

Requirements

• You need an Advanced degree in quantitative field or equivalent experience.
• You need + years of pricing or retail analytics experience.
• You need Strong SQL and Python/R skills for data analysis.
• You need Experience with experimental design (A/B tests) and causal inference.
• Ability to translate business problems into analytical plans and drive decisions.
• You need Technical judgment and risk assessment for pricing decisions.
• You need Preference for candidates with background in e-commerce or retail.

Nice to have

• It helps if Experience with pricing optimization platforms and tools.
• It helps if Background in margin management or contribution margin analytics.
• It helps if Familiarity with portfolio brand operating models.

Practical notes

Note: For , Lead pricing science and experimentation for portfolio brands.

Develop causal and predictive models to optimize pricing and promotions.

Partner with merchandising and finance to set pricing strategy and guardrails.

Design A/B tests and analyze results to inform pricing decisions.

For , Build and maintain pricing analytics dashboards and tools.

For , Communicate insights and recommendations to cross-functional stakeholders.

For , Advanced degree in quantitative field or equivalent experience.

For , + years of pricing or retail analytics experience.

For , Strong SQL and Python/R skills for data analysis.

For , Experience with experimental design (A/B tests) and causal inference.

Ability to translate business problems into analytical plans and drive decisions.

For , Technical judgment and risk assessment for pricing decisions.

For , Preference for candidates with background in e-commerce or retail.

For , Experience with pricing optimization platforms and tools.

For , Background in margin management or contribution margin analytics.

For , Familiarity with portfolio brand operating models.

For , SQL.

For , Python.

For , R.