In March 2015, Turnkey Sports & Entertainment (Turnkey) was named by Forbes as one of the 10 Best Organizations to Work for in Sports. An established, industry-leading firm, Turnkey is a nimble, innovative company with a young core. We build our own software products, license other and offer a solutions-based research approach to a diverse landscape of clients in sports and entertainment. Our research group lies at the heart of everything we do.
For 20 years, Turnkey has been at the forefront of market research in sports and entertainment, becoming a trusted brand for smart, actionable business intelligence. Our clients value our triumvirate of specialties: sports and live entertainment, marketing, and consumer research. Turnkey specializes in services and software that enable properties, sponsors, venues, agencies, and other entities within sports and entertainment to monetize insights for improved business performance. We are a growing, dynamic and curious entrepreneurial company, which is looking to add a critical member to our research team.
Turnkey’s leadership and expertise in the sports marketing sector provides customized branding and sponsorship research for a variety of clients across every permutation of the industry. Over the last two decades, we have conducted hundreds of custom research studies for the league offices and the teams in MLB, MLS, NBA, NFL and NHL. With sponsorship impact studies performed for clients from AT&T, UPS and Hyundai, to media clients including ESPN and NBC Sports, Turnkey’s sponsorship expertise expands upon our already well-established property research experience.
Located in the quaint Philadelphia suburb of Haddonfield, NJ, Turnkey is looking for our next impactful team member to expand our presence with clients looking to drive insights for current or potential clients in the sports and entertainment industry.
Develop and maintain a deep understanding of clients’ businesses and a strong knowledge of new and emerging analytic solutions that will drive actionable insights. Build, deliver and maintain high quality analytic databases to support complex analytics with a focus on individual level and/or aggregated marketing effectiveness and attribution. Extract actionable information from data, model complex systems, and scale these processes to large data sets. Work with a team of marketing strategists and scientists to assess data for solving C-level marketing investment questions. Hands-on management of client projects from data assessment and analysis to delivering final analytic datasets with a hyper-focus on quality and service.
ESSENTIAL DUTIES AND RESPONSIBILITIES:
- Understands how to leverage existing and new, innovative approaches to address business challenges and market opportunities (i.e. brand equity, marketing mix and pricing models)
- Design, specify and develop models, optimization algorithms, and highly scalable processes for marketing measurement
- Client-facing, trusted business partner who is regarded as a domain expert, able to translate expertise into actionable, analytic insights to drive clients’ business performance.
- Work closely with product and client teams to develop new service offerings by building and enhancing the value and breadth of the current solutions
EXPERIENCE AND SKILLS:
- At least three years of experience working on data-intensive analytics solutions that include building marketing mixed models, experience with CPG, durable goods and/or services econometric models preferred
- Able to engage in a consultative manner across multiple levels (c-suite to end user) with a strong executive presence, demonstrating strong
presentation and influencing skills
- Experience working on large distributed datasets using Hadoop, HiveSQL, Spark, Python, Scala, R, and Matlab is preferred
- Superior understanding of client issues at both strategic and business-building levels.
Exceptional problem-solving skills and high-level business savvy.
- Experience working with commercial and/or open source statistics and data mining packages Ph.D. or Master’s degree in Data Science, Statistics, Engineering or a related field is preferred