Senior Data Scientist

Job Duties: Develop, validate, and maintain machine learning models that support business strategies and decisions. Design experiments or use causal inference methods to measure the effectiveness of improvements to the SeatGeek product, applying regression analysis and A/B testing to identify opportunities for optimizing UI/UX across the website and mobile app. Develop research questions and conduct data analysis to generate insights and recommendations that help SeatGeek make smarter decisions and enhance operational efficiency. Define, evaluate, and monitor key metrics, understanding the root causes of changes, and feeding them back to business stakeholders to action on. Participate in the design and implementation of SeatGeeks event recommendation system, leveraging artist similarity metrics and user behavioral data to drive personalized recommendations. Work closely with the Analytics Engineering team to build lasting, analysis-friendly data models and performant batch models that run in production. Contribute to the development of the Product Analytics function and the wider data community at SeatGeek with programming and problem-solving best practices. Partner with stakeholders on the Product team, understanding their objectives and aligning our work to complement and enhance their ability to achieve those goals. Telecommuting Permitted.Minimum Requirements: Bachelors or foreign equivalent degree in Computer Science, Data Science, Math, Statistics, or in a related field and 5 years of progressive, post-baccalaureate experience in the job offered or in a computer-related occupation.Special Requirements: Position requires experience, coursework, or knowledge in each of the following skills: 1. Using SQL for data transformation and optimization; 2. Modern data warehouse and lake architectures including Redshift, Snowflake, or Databricks; 3. Developing and maintaining robust ETL/ELT pipelines using tools including DBT and Airflow to ensure reliable and performant data workflows; 4. Designing scalable, modular data models including Star or Snowflake schemas; 5. Building scalable frameworks using Python scripting, automation, and object-oriented programming; 6. Applying data science to business problems including pricing optimization, event recommendations, and broker recognition; 7. Building dashboards and visualizations using tools including Looker, Tableau, Superset, or Hex, and Python libraries including Matplotlib and Plotly; and 8. Working on user growth in a customer-facing digital product and optimizing the full user lifecycle funnel including Acquisition, Activation, and Retention.Employment and background checks may be required. Standard Benefits. To apply, all applicants must submit resume to https://www.jobpostingtoday.com/ & reference ID#. Employment & background checks may be required.