LA Kings - Sr. Data Analyst

<p><strong>Company Information</strong><br>For more than 20 years, AEG has played a pivotal role in transforming sports and live entertainment. Annually, we host more than 160 million guests, promote more than 10,000 shows and present more than 22,000 events around the world. We are committed to innovation, artistry, and community, and leverage the power of our 300+ venues, leading sports franchises, marquee music brands, integrated entertainment districts, premier ticketing platform and global sponsorship activations, to create memorable moments that give the world reason to cheer.</p> <p>Our business is interwoven with the human mind and heart, and we strive to build a diverse and inclusive company that reflects the artists, athletes, and fans that we host; reach beyond traditional boundaries to support the communities in which we operate; and minimize our impact on the environment by adopting sustainable practices throughout our business operations.<br><br>If you want to be challenged to up your game and make a difference, then join us in giving the world reason to cheer!</p> <p><u>JOB DESCRIPTION:</u></p> <p>The Sr. Data Analyst will play a pivotal role in maximizing revenue and driving dynamic pricing strategy across ticketing products and fan segments. Using statistical modeling and machine learning, this role will measure price elasticity, forecast revenue, and predict customer demand. The position will collaborate closely with cross-functional teams, including Sales, Service, Marketing, and Operations, to deploy scalable data science tooling, drive decision-making, and optimize sales.</p> <p>&nbsp;<u>ESSENTIAL FUNCTIONS:</u></p> <ul> <li><span data-contrast="auto"><span data-ccp-parastyle="No Spacing">Implement and manage dynamic pricing</span><span data-ccp-parastyle="No Spacing">&nbsp;</span><span data-ccp-parastyle="No Spacing">mechanisms</span><span data-ccp-parastyle="No Spacing">&nbsp;to</span><span data-ccp-parastyle="No Spacing">&nbsp;adjust ticket prices in real-time based</span><span data-ccp-parastyle="No Spacing">&nbsp;</span><span data-ccp-parastyle="No Spacing">on factors such as team performance, opponent strength, and event timing</span><span data-ccp-parastyle="No Spacing">.</span></span><span data-ccp-props="{&quot;201341983&quot;:0,&quot;335559739&quot;:0,&quot;335559740&quot;:240}">&nbsp;</span></li> <li><span data-contrast="auto"><span data-ccp-parastyle="No Spacing">Utilize models and data analysis to&nbsp;</span><span data-ccp-parastyle="No Spacing">identify<