As a Level II Pricing Scientist, you will take ownership of key analytical projects, drive the deployment of pricing engines, and lead A/B testing strategies for a Fortune 500 retail food client. This role is ideal for a mid-career pricing professional with experience developing and scaling pricing models, executing pricing strategies, and communicating data-driven insights across departments. You will work in close collaboration with engineering, marketing, product, and finance to ensure pricing strategies align with market dynamics and revenue goals. This role is ideal for a pricing professional with strong experience in testing frameworks and causal inference, capable of translating experimentation into actionable pricing strategy.

Responsibilities

• Drive functional deployment and enhancement of pricing engines in new markets.
• Conduct structured UAT and pricing engine testing to validate outputs.
• Refine and optimize Python-based EDA tools to monitor pricing engine performance.
• Develop and iterate on pricing recommendation models based on elasticity and segment behavior.
• Design and execute A/B testing frameworks to evaluate price and promotion effectiveness.
• Apply causal inference methodologies to isolate the true impact of pricing and promotional actions.
• Analyze market dynamics, customer behavior, and pricing sensitivity to drive strategic insights.
• Collaborate with data engineers to ensure clean, high-quality input for pricing engines.
• Automate pricing performance reports and monitoring dashboards for market and executive use.
• Support integration of new data sources and templates into analytics workflow.
• Develop stakeholder-facing dashboards and strategic reporting decks.
• Communicate pricing strategy insights with mid-level and senior stakeholders.
• Support change management and training for market onboarding to new pricing platforms.

Soft Skills

• Strong business acumen and ability to align analytics with commercial goals.
• Excellent written and verbal communication with technical and non-technical stakeholders.
• Problem-solving mindset with a proactive approach to innovation.
• Ability to manage multiple projects and deadlines with minimal supervision.

Required Qualifications

• Bachelor’s or Master’s degree in a quantitative discipline.
• 5–8 years of hands-on pricing analytics or data science experience.
• Strong coding skills (Python, R, SQL) and familiarity with BI tools (Power BI, Tableau).
• Experience with A/B testing, time series forecasting, and pricing optimization techniques.
• Understanding of optimization techniques and market economics.
• Experience with experimental design, statistical testing, and causal inference methodologies (e.g., uplift modeling, diff-in-diff, propensity scoring).

Preferred Qualifications

• Master’s degree in Business Analytics, Economics, Applied Mathematics, or related field.
• Experience with pricing tools (PROS, Vendavo, Zilliant) or dynamic pricing platforms.
• Familiarity with cloud-based data platforms (GCP, AWS, or Azure).
• Exposure to conjoint analysis or discrete choice modeling techniques.
• Advanced experience applying causal inference techniques in pricing or promotion analytics.