About the position
StubHub is on a mission to redefine the live event experience on a global scale. Whether someone is looking to attend their first event or their hundredth, we're here to delight them all the way from the moment they start looking for a ticket until they step through the gate. The same goes for our sellers. From fans selling a single ticket to the promoters of a worldwide stadium tour, we want StubHub to be the safest, most convenient way to offer a ticket to the millions of fans who browse our platform around the world. As a Senior Data Scientist in Performance Marketing, you will utilize SQL and programming languages for data science (including Python and R), and numerical and scientific libraries used for statistics and machine learning (including Pandas, NumPy, SciPy, and scikit-learn). You will transform and analyze large scale data with modern cloud computing platforms (including SparkSQL, BigQuery, Snowflake, and Redshift). You will build interactive reports and reusable analyses with advanced notebook tools (including Hex, Colab, Mode, and Jupyter). You will train and build production level models in cloud environments (including AWS and Azure) using orchestration software (including Metaflow and Airflow). You will perform time series modeling (including GAMs, GLMs, and ARs) and real-time forecasting. You will work with non-technical stakeholders to understand, anticipate, and deliver on their data needs. You will own one or more business domains, building deep industry expertise, anticipating the needs of that vertical's leader, and being the data science thought leader. You will collaborate cross functionally with engineering, business, and product teams, oftentimes acting as proxy for one or the other. Up to 10% travel required to corporate headquarters located in New York, New York and the company's other domestic offices in the United States. Telecommuting may be permitted up to 2 days per week. When not telecommuting, must report to StubHub, Inc. at 120 Broadway, 2nd Floor, Santa Monica, CA 90401.
Responsibilities
- Utilize SQL and programming languages for data science (including Python and R).
- Transform and analyze large scale data with modern cloud computing platforms (including SparkSQL, BigQuery, Snowflake, and Redshift).
- Build interactive reports and reusable analyses with advanced notebook tools (including Hex, Colab, Mode, and Jupyter).
- Train and build production level models in cloud environments (including AWS and Azure) using orchestration software (including Metaflow and Airflow).
- Perform time series modeling (including GAMs, GLMs, and ARs) and real-time forecasting.
- Work with non-technical stakeholders to understand, anticipate, and deliver on their data needs.
- Own one or more business domains, building deep industry expertise.
- Collaborate cross functionally with engineering, business, and product teams.
Requirements
- Bachelor's degree or U.S. equivalent in Mathematics, Statistics, Computer Science, or a related field.
- 5 years of professional experience as a Data Scientist, Decision Scientist, or any occupation/position/job title involving data science, machine learning, and experimentation.
- 5 years of professional experience utilizing programming languages for data science (including Python and R) and markdown configuration files (including YAML).
- 5 years of professional experience orchestrating machine learning models using Airflow.
- 5 years of professional experience building reusable reports and application prototypes for technical and non-technical stakeholders with notebook tools (including Hex).
- 5 years of professional experience using distributed query services (including Athena and SparkSQL) to transform large data sets.
- 5 years of professional experience leveraging advanced statistics and scientific libraries (including Pandas, NumPy, SciPy, and scikit-learn) to drive insights for decision-making.
- 5 years of professional experience building time series models (including GAMs, GLMs, and ARs) and real-time forecasts.
- 1 year of professional experience leveraging Snowflake SQL and Snowpark to transform and analyze large sets of data.
- 1 year of professional experience training and productizing machine learning models using Metaflow.
Benefits
- Equity
- 401(k)
- Paid time off
- Paid parental leave
- Comprehensive health benefits
