Pricing Strategy Analyst

Accountabilities: As a Pricing Strategy Analyst, you will support the development and optimization of pricing strategies, evaluate commercial opportunities, and deliver data-driven insights that help improve revenue, margins, and customer acquisition.

• Develop strategic business cases for new products, pricing initiatives, promotional offers, and customer acquisition strategies.

• Support key pricing decisions, including acquisition pricing, base pricing, annual price increases, fee adjustments, and alternative pricing models.

• Structure complex or ambiguous business problems, evaluate potential solutions, and deliver clear, data-supported recommendations to leadership.

• Build financial models and conduct scenario analyses to assess market opportunities, forecast financial outcomes, and estimate the return on investment of strategic initiatives.

• Analyze pricing performance, promotional effectiveness, competitive positioning, customer behavior, and acquisition trends across products and customer segments.

• Use advanced Excel and financial modeling as primary analytical tools, leveraging SQL, Python, Power BI, Tableau, and existing reporting resources where appropriate.

• Design and support pricing experiments, including test planning, measurement frameworks, post-launch analysis, and optimization recommendations.

• Evaluate pricing elasticity, customer segmentation, promotional results, and revenue trends to inform commercial decisions.

• Develop dashboards, recurring reports, and performance monitoring tools to track pricing, revenue, margin, and customer metrics.

• Prepare executive presentations and visualizations that communicate complex findings clearly and translate analysis into actionable business recommendations.

• Collaborate with Product, Marketing, Finance, Sales, and Analytics teams to define business requirements and prioritize strategic initiatives.

• Leverage AI productivity tools, including ChatGPT and Microsoft Copilot, to accelerate research, automate analysis, improve content development, and increase efficiency.

• Identify opportunities to improve analytical workflows, reporting processes, and business decision-making capabilities.

Requirements:

The ideal candidate combines strong financial acumen, advanced analytical skills, and business judgment with the ability to communicate insights effectively and navigate complex, evolving priorities.

• Bachelor’s degree in Business, Economics, Finance, Analytics, Marketing, Data Science, or a related field.

• Typically 3–6 years of relevant experience in pricing, strategy, business analysis, consulting, financial analysis, product strategy, or analytics. Candidates will be considered flexibly based on demonstrated skills and ability to perform the role.

• Experience developing financial models, business cases, forecasts, scenario analyses, and executive-level presentations.

• Experience supporting pricing, customer acquisition, product, or commercial strategy initiatives.

• Strong business acumen and the ability to translate analytical findings into practical strategic recommendations.

• Advanced Excel skills, including financial modeling, forecasting, and scenario analysis.

• Strong PowerPoint and presentation skills, with the ability to simplify complex analyses and communicate recommendations clearly to senior stakeholders.

• Excellent analytical thinking, structured problem-solving, and financial reasoning skills.

• Ability to work effectively with ambiguity, manage multiple initiatives, and collaborate across functions in a fast-paced, data-driven organization.

• Ability to work independently in a remote environment while maintaining strong cross-functional relationships.

Preferred qualifications:

• An MBA or other relevant advanced qualification.

• Experience with pricing experimentation, price elasticity analysis, customer segmentation, promotional analysis, or revenue optimization.

• Experience in subscription-based, media, telecommunications, technology, consumer services, or other recurring-revenue businesses.

• Familiarity with SQL for data extraction and analysis; this is an advantage rather than a core requirement.

• Experience using Python for data analysis and automation; advanced coding capabilities are a plus but not essential.

• Experience building dashboards and executive reporting in Power BI and/or Tableau.

• Familiarity with AI productivity tools such as ChatGPT and Microsoft Copilot, including effective prompting and using AI to accelerate analytical work.

• Willingness and ability to learn new AI-enabled workflows and emerging analytical tools quickly.

Benefits:

• Annual compensation: $140,000–$165,000.

• Work arrangement: Fully remote within the United States, with work scheduled around U.S. time zones.

• Employment type: Full-time position initially planned for approximately 12 months, with potential for extension.

• Healthcare and well-being: A competitive benefits package designed to support employees’ health and overall well-being.

• Professional growth: Opportunities to develop analytical, strategic, and financial modeling expertise while contributing to high-impact business decisions.

• Collaborative environment: Work cross-functionally with teams across pricing, product, marketing, finance, sales, and analytics.

• Work-life considerations: Weekend work is uncommon and may be required only occasionally.

How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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