Job Type Full-time Description As a Strategic Pricing Analyst / Manager, you’ll partner with our Product Managers, Sales Leaders Marketing, and Data Engineering teams to accelerate pricing gains through finely tuned, data-driven pricing and promotional strategies. You will leverage vast, structured and unstructured datasets spanning transaction history, competitive benchmarks, customer feedback and more to uncover insights, drive automated pricing systems, and inform decisions at every stage of the customer journey. Essential Duties And Responsibilities Pricing Strategy & Deployment Integrate product and customer segmentation and competitive benchmarking with realized-price (list-to-net) gap analysis, margin-lever optimization, and product-capability valuation into a unified framework that drives both strategic and day-to-day pricing decisions. Experiment Design & Analysis Product Management, Sales and Marketing to ideate, run and measure A/B and multivariate pricing experiments, testing hypotheses around price elasticity, bundling, discounting and value-based segmentation. Daily Pricing Operations Own the data inputs and reporting that inform day-to-day price adjustments: monitor competitor moves, customer response patterns and margin impact across direct, distribution, and e-commerce channels. Advanced Modeling & Performance Tracking Build and maintain statistical and machine-learning models to quantify price sensitivity, forecast demand, quantify experiment lift, and continuously iterate on strategy. Tools & Infrastructure Roadmap Collaborate with Data Engineering to shape our pricing engine and analytics stack—design controls, dashboards, automated pipelines, and streaming-data workflows. AI/ML Use-Case Deployment Drive cross-functional pilots of new AI techniques (e.g., reinforcement learning for dynamic pricing, LLM-powered deal guidance), capture learnings, and build roadmaps for broader rollout. Third-Party Pricing Software Evaluation & Selection Conduct feature-matrix assessments and scorecard evaluations against criteria such as ease of integration (ERP/CRM), flexibility of discount rules, real-time insights and user-experience. Own the vendor demo, proof of concept and RFP process. Cross-Functional Partnership Liaise with Finance, Sales, Order Entry and Product Management to align pricing guardrails, discount authorities and go-to-market packaging with overall business goals. Market Intelligence & Scenario Planning Stay abreast of competitor pricing tactics, macroeconomic trends and customer needs; run scenario analyses to assess potential P&L impacts. Requirements Qualifications and Requirements • Experience: 3–5 years in pricing analytics, revenue operations or related data-driven field. • Education: Bachelor’s degree in business, Finance, Economics, Data Science or a related field; MBA or advanced analytics certification a plus. • Analytical Rigor: Proven track record driving pricing or monetization initiatives end-to-end strategy, experimentation, modeling and operationalization. • Business Acumen: Experience in interpreting P&L and margin metrics to balance top-line growth against bottom-line impact and understanding market and competitive intelligence impacting pricing. • Communication: Excellent verbal and written skills; adept at storytelling with data and presenting to executive teams. • Collaboration: Demonstrated ability to work cross-functionally with Product Management, Sales, Finance and Data Engineering to align pricing objectives. Technical Skills • Data Manipulation: Expert in SQL and Python (pandas, NumPy), with experience building and testing robust analytical workflows. • Cloud & Big Data: Familiarity with AWS services (Redshift, S3, Glue, EMR, Kinesis, Firehose, Lambda, IAM), or equivalent cloud platforms. • Orchestration & Streaming: Experience with Airflow (or similar) for pipeline scheduling—and with streaming-data processing frameworks. • BI & Visualization: Hands-on with Tableau, Power BI or comparable tools to craft interactive dashboards and executive-ready reports. • Statistical & ML Methods: Comfort applying regression, clustering, NLP or other ML techniques to unstructured and time-series data. Desired Characteristics • Resourceful & Agile: Tackle ambiguity head-on, adapt quickly to shifting priorities, and leverage existing tools to deliver impact. • Strategic Mindset: Able to “zoom out” for the long-term pricing objectives while also digging into daily operations and tactical experiments. • Collaborative Team Player: Earn trust across geographies and functions; mentor peers and share best practices in pricing science. • Professional & Discreet: Handle confidential data and high-visibility projects with utmost integrity and confidentiality.