Senior/Lead Data Scientist- Pricing Optimization

Location: New York, New York, United States, Chicago, Illinois, United States, California, United States

Department: Data Science

Workplace: remote

Employment Type: full

Description

Tiger Analytics is pioneering what AI and analytics can do to solve some of the toughest problems faced by organizations globally. We develop bespoke solutions powered by data and technology for several Fortune 100 companies. We have offices in multiple cities across the US, UK, India, and Singapore, and a substantial remote global workforce.

We are also market leaders in AI and analytics consulting in the CPG & retail industry with over 40% of our revenues coming from the sector. This is our fastest-growing sector, and we are beefing up our talent in the space.

We are seeking an experienced Data Science Lead to lead our Pricing and Promotion Optimization team. In this role, you will drive the development and execution of product strategies that enhance pricing and promotion initiatives. The ideal candidate will have a strong background in product management with a focus on analytics-driven decision-making, as well as proven experience in roadmap planning and cross-functional team leadership.

Key Responsibilities:

• Work on the latest applications of data science to solve business problems in the optimization space for a CPG client
• Effectively communicate the analytics approach and how it will meet and address objectives to business partners.
• Product Roadmap Development: Create, manage, and communicate a clear roadmap and strategic vision for the pricing and promotion optimization product, aligned with business goals and market trends. Key activities include developing, maintaining, enhancing and scaling the product to various Markets.
• Quarterly Planning: Design and implement quarterly plans, ensuring alignment with product goals, KPIs, and timelines.
• Team Leadership: Lead and mentor a cross-functional team of 5-6 members, fostering a collaborative and high-performance environment.
• Pricing & Promotion Strategy: Define and implement an optimization framework to optimize pricing and promotional Strategies.
• Stakeholder Collaboration: Work closely with internal teams, including Marketing, Sales, Engineering, and Analytics, to gather requirements and translate them into actionable plans.
• Market and Competitive Analysis: Conduct ongoing analysis of market trends and competitor strategies to identify opportunities and gaps.
• Performance Monitoring: Track and analyze key metrics to ensure product success, and identify areas for improvement to drive product growth.
• Collaborate, coach, and learn with a growing team of experienced Data Scientists.
• Stay connected with external sources of ideas through conferences and community engagements.
• Support demands from regulators, investor relations, etc., to develop innovative solutions to meet objectives utilizing cutting-edge techniques and tools.

Requirements

• 10+ years of Data Science experience, and 8+ years of experience in product management, with a focus on pricing, promotions, or optimization.
• Graduate Degree in Data Science, Computer Science, or a related field is required
• Proven experience managing a team and leading product initiatives.
• Skilled in creating product roadmaps, setting priorities, and executing strategic plans.
• Proven experience managing a team and leading product initiatives.
• Analytical Mindset: Strong data analysis skills, with experience in pricing strategies and optimization.
• Exceptional communication and collaboration skills to understand business partner needs and deliver solutions.
• Experience in Azure environments and Databricks is a plus
• Bias for action, with the ability to deliver outstanding results through task prioritization and time management.
• Be proactive, curious, can-do attitude, flexible personality

Benefits

This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.