THE COMPANY: SCOREBIG, INC.

Founded in 2009, ScoreBig is the leading eCommerce marketplace for live event tickets.  Built on an innovative pricing model and proprietary pricing engine, ScoreBig allows fans to purchase live event tickets at below box office prices, by naming the price they are willing to pay for tickets.  The Company offers fans savings of up to 60% off of box office prices for thousands of events nationwide.  ScoreBig is the first and only sales channel available for the $40 billion ticket industry, allowing sports, arts, music and theater organizations to move unsold tickets without the price and brand degradation inherent in traditional “discounting”.

The Company has built a strong foundation of primary partnerships across many of the largest sports, music and theater properties in the U.S. and maintains direct relationships with over 100 of the leading ticket brokers, ensuring expansive coverage of the live entertainment market.  ScoreBig has 95% coverage of all major US Professional sports - MLB, NBA, NHL and NFL.

ScoreBig is rapidly growing and looking for sharp, dedicated and self-motivated people to help take the Company to the next level.

Highlights:

• ScoreBig was recently recognized by Forbes as one of America’s Most Promising Companies.
• Offers over 1 million live event tickets for sale across the U.S.
• Significant funding from leading venture capital firms Bain Capital Ventures & U.S. Venture Partners, along with other industry veterans.
• Led by a proven executive team with deep experience in sports, entertainment, ticketing, internet and technology businesses and a world-class advisory board.
• See additional press here.

The Data Science Analytics Manager will be responsible for creating a procedure that allows the company to acquire and manage ticket inventory effectively.  Develop and implement analytical methods on inventory assortment, promotions and visual merchandising to improve business performance.  Conduct ongoing exploratory data analysis to then build effective models for solving business problems.

Specifically…

• Analyze pricing & inventory trends across live entertainment – sports, concerts, theatre & family events to provide insights for both ScoreBig internal pricing & partners (teams, leagues, promoters).
• Work with technology team on building the ScoreBig Big Data infrastructure by proving business requirements and use cases.
• Build predictive models & segmentation models to answer key business questions such as:
  • “How do we identify customers with a propensity to buy at full price retail? “
  • “What level of ticket availability & pricing can we expect by season? “
  • “What factors influence a purchase decision on ScoreBig? “
  • “What different ticket buying customer segments exist and what factors drive their ticket purchase decisions how does pricing elasticity vary by season? “
  • Work with product team to both design & analyze optimization (A/B testing) experiments for ScoreBig.com

• EDUCATION: BA/BS in mathematics, economics or a suitable quantitative discipline.  Advanced degree is a plus.
• EXPERIENCE: 5+ years of relevant experience in business modeling and management, with extensive experience in quantitative analytical model development and implementation.
• Experience with statistical language (SAS, R, SPSS).
• Strong MS Excel skills, statistical software exposure, SQL experience is required (SQL Server preferred, but Oracle and MySQL are OK).
• Big data infrastructure and ecommerce experience is a plus.
• Excellent verbal and written communicator able to work effectively across the organization. 
• Entrepreneurial drive and demonstrated ability to achieve stretch goals in an innovative and fast-paced environment.
• Possess distinctive problem solving, organizational and analytical skills.
• A self-starter who takes initiative and possess an entrepreneurial spirit.
• Smart and driven individual that knows what needs to be done and operates with a sense of urgency, focus and discipline.
• Able to work well with ambiguity and comfortable dealing with changes and juggling competing priorities.
• Doesn’t understand 9 to 5, passionate about technology and very results oriented.