When your team hits a game-winner or the band plays your favorite song, there is nothing like experiencing the moment live and in-person. At “Experience”, expapp.com, our mission is to connect people to those unforgettable live experiences with mobile technology and move people from the couch to the crowd. Whether it’s securing tickets, upgrading to a fantastic seat, or participating in a once in a lifetime experience, sports and entertainment companies and fans alike realize that these opportunities should no longer be wasted.
We are looking for an experienced Data Scientist to join our rapidly growing team! Candidates musthave a passion for all things data and be ready to create next-generation data science to power a company reshaping an industry. This role offers the unique opportunity to disrupt the 20-billion dollar ticketing industry with innovative technology and be part of a fast-paced, collaborative team.
In this exciting role, you will:
- Create predictive models to power innovative ticketing products
- Acquire and explore data from creative sources to power data science initiatives
- Create data pipelines and applications in Amazon Web Services environments
- Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies
- Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes
- Coordinate with different functional teams to implement models and monitor outcomes
- Develop processes and tools to monitor and analyze model performance and data accuracy
- Interact with project stakeholders to provide data science solutions addressing business requirements
- Bachelor’s degree
- 3-7 years of data science and analytics experience
- Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.
- Experience creating and deploying data science solutions in a cloud environment (AWS preferred)
- Experience using statistical computer languages (Python, SQL, Scala) to manipulate data and draw insights from large data sets
- Experience working with and creating data architectures
- Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks
- Experience visualizing/presenting data for stakeholders using: Tableau, Excel, etc.
- Strong problem-solving skills with an emphasis on product development
- Excellent written and verbal communication skills for coordinating across teams
- A drive to learn and master new technologies and techniques
Nice to Have:
- Advanced degree in math, statistics computer science, economics or another data-related field
- Experience with multiple AWS products: Lambda, Sagemaker, Athena, EC2, EMR, Redshift, Glue, S3
- Experience managing digital data across web pages and mobile applications
- Tableau experience
- Experience in digital analytics tools: Google Analytics, Adobe Analytics, MixPanel, etc.
- Work with a proven and incredibly talented team
- Medical / Dental / Vision coverage and 401K match
- INWEGO membership for you and a plus one
- In-office massage therapists
- Work on a new MacBook Pro Retina Laptop
- Open, fun and comfortable workspace (no cubes!)
- We have a coffee bar that keeps us going with beverages and healthy snacks
- 75″ Television in work area for work demos & maybe for watching Football too
- Break-out rooms for small meetings, privacy, quiet space
- We have a robot and he pushes code, makes jokes, and runs our automated tests!
- Ping-pong table, XBOX, and Nintendo 64 (bring your A game!)
- Be the DJ with Sonos throughout the office
- Pennant of your university hung with pride in the office
Equal Employment Opportunity (EEO):
We’re an equal opportunity employer and comply with all applicable federal, state, and local fair employment practices laws. We strictly prohibit and do not tolerate discrimination against employees, applicants, or any other covered persons because of race, color, religion, creed, national origin or ancestry, ethnicity, sex, gender (including gender nonconformity and status as a transgender or transsexual individual), sexual orientation, marital status, age, physical or mental disability, citizenship, past, current or prospective service in the uniformed services, predisposing genetic characteristic, domestic violence victim status, arrest records, or any other characteristic protected under applicable federal, state or local law.