Pricing Analyst II

Role Overview: As a Pricing Analyst / Business Analyst, you will be responsible for developing pricing strategies, researching various dimensions of ratemaking, and comparing cost factors. Your role will involve working independently while also collaborating within a team environment that may include Engineering, Sales, and Customer Service departments. Key Responsibilities: - Exhibit strong critical thinking, problem-solving, and technical knowledge to challenge business assumptions and develop new methods, statistical models, and analyses that inform pricing policies, strategies, and customer programs. - Demonstrate a continuous learning mindset and a customer-centric approach to synthesize large datasets and translate analyses into actionable insights. - Establish scalable, efficient, user-centric, and automated processes for large-scale data analyses to support business processes and decision-making. - Analyze and review current and future state pricing models, examine competitor pricing, and suggest pricing structures and models. - Track pricing and price changes based on commodity and material input changes. - Apply statistical modeling methods to determine the potential impact of pricing strategies on current and future pricing. - Collaborate with sales and marketing departments to develop and implement competitive pricing strategies. - Develop dynamic pricing tools to effectively respond to changing market needs and trends. - Provide insights and perspectives on various dimensions of ratemaking and pricing strategy through research and analysis. - Support cross-functional teams in resolving complex issues through problem-solving and decision support with clear communication and proposed recommendations to leadership. Qualifications Required: - Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Finance, Economics, or other quantitative related fields. - Minimum of 8 years of relevant experience in a pricing and statistical analyst role. - Experience in conducting quantitative analysis, developing analytical models, dashboards, data visualizations, and decision-making tools. - Proficiency in using statistical computer languages (R, Python, SQL, etc.) to manipulate data and draw insights from large datasets. - Experience in developing and optimizing Excel macros, VBA, and Power BI dashboards. - Experience with experimentation, such as A/B testing experiment design. - Ability to synthesize data, research, and analyses into simple, concise, accessible, and actionable insights. - Strong critical thinking, problem-solving, and analytical skills. - Strong verbal, written, and presentation communication skills. - Strong interpersonal and influencing skills.,