What is a Pricing Data Scientist I (Senior Pricing Analyst)?

The ideal candidate will be a highly motivated leader and problem-solver who works cross functionally across various department. As a Data Scientist, you will find yourself in a unique position of designing a pricing strategy by leveraging data science and analytics power while incorporating partner team objectives to ultimately deliver value for our customers.

You will use qualitative and data analytics to design strategy and actions and champion cross functional initiatives.

Responsibilities:

• Work across business leadership, internal stakeholders to define and support strategic competitive intelligence and pricing priorities.
• Champion cross functional initiatives with Marketing, Finance, and Operations, translate pricing data and analytic insights into actionable business processes.
• Able to manage sophisticated analytical exercises to drive actionable insights, outcome, and business decision-making in the fields of Pricing and Promotions.
• Define, document processes ensuring business continuity while gaining efficiency in the processes.

Requirements:

• Masters in Statistics, Mathematics, Computer Science, Economics, Business Administration, Engineering, Finance, or related disciplines.
• 2 years of related work experience and demonstrated track record of innovation and impact and proficiency in SQL, Python, Alteryx, Data Visualization tools and statistical tools.
• Strong analytical skills & creative problem solver that can turn data into actionable insights.
• Ability to explain statistical approaches/models used, rationale/merits of different approaches, results and interpretation to team members.
• High attention to detail and proven ability to manage multiple, competing priorities simultaneously. Ability to quickly adapt to changing priorities and generate innovative solutions in a fast-paced environment.
• Experience with pricing analytics and data science methodologies including promotion and demand elasticity models.
• Experience with customer segmentation, competitive analysis, and customer behavior analysis.