Senior Data Scientist

The National Basketball Association (NBA) is a global sports and media organization with the mission to inspire and connect people everywhere through the power of basketball. Built around five professional sports leagues: the NBA, WNBA, NBA G League, NBA 2K League, and Basketball Africa League, the NBA has established a major international presence with games and programming available in 215 countries and territories in more than 50 languages, and merchandise for sale in more than 200 countries and territories on all seven continents. NBA rosters at the start of the 2021-22 season featured a record 121 international players from 40 countries. NBA Digital’s assets include NBA TV, NBA.com, the NBA App, and NBA League Pass. The NBA has created one of the largest social media communities in the world, with 2.1 billion likes and followers globally across all league, team, and player platforms. Through NBA Cares, the league addresses important social issues by working with internationally recognized youth-serving organizations that support education, youth and family development, and health-related causes. The NBA is committed to providing a safe and healthy workplace. To safeguard our employees and their families, our visitors and the broader community from COVID-19, and in consideration of recommendations from health authorities and the NBA’s own advisors, any individual working onsite in our New York and New Jersey offices must be fully vaccinated against COVID-19, including having received a booster when eligible. The NBA will discuss accommodations for individuals who cannot be vaccinated due to a medical reason or sincerely held religious belief, practice, or observance. Position Summary: This position is part of an expanding data science and data product team with the mission to discover, inspire and engage fans around the world. We are searching for a strategic and inquisitive senior data scientist to develop and run with fan data centered projects. As part of this team, you will create models to build a more personalized experience for our fans including but not limited to models that predict conversion, retention, and viewership. The team also builds and maintains tools that bring these models together to predict the lifetime value (and other related key metrics) of fans. You'll work closely with partners across engineering, marketing, DTC, social media, and other data science teams to support different business cases and optimize business outcomes. This is a rare opportunity as the solutions you help develop and deploy will have a real and immediate impact on both the league's fans and internal business operations. Major Responsibilities: Develop predictive models and robust analytics to support analytic insights and visualization of complex data sets Provide optimization recommendations that drive KPIs established by stakeholders Innovate by exploring new experimentation methods and statistical techniques that could sharpen our decision-making processes Develop and deploy testing hypotheses and analyze test results, providing the necessary analytical rigor to ensure data quality, consistency, repeatability, and accuracy of insights Required Skills/Knowledge: You embrace the player and coach mindset - taking the lead on solving hard problems to further your own professional development while mentoring those around you in their growth trajectories You care just as much about why you're solving a problem as the types of problems You want to understand context and the bigger picture of how the problem you're working on is impacting and benefitting our members You find yourself often building tools to help others solve their problems and try to follow a philosophy of continuous improvement and automation You want to continue to grow and optimize to your learning rate and are excited by hard problems and big challenges Experience in one or more of the following in a professional capacity: customer modeling (LTV, Churn), time series prediction, natural language processing and classification, machine learning applied to consumer products 5+ years of professional experience working in a data science capacity with some combination of Python/scripting language and relational database production experience Experience in one or more of the following in a professional capacity: customer modeling (LTV, Churn), time series prediction, natural language processing and classification, machine learning applied to consumer products Education: Bachelor's Degree or equilvaent experience Salary: $140,000 to $175,000 per year We Consider Applicants For All Positions On The Basis Of Merit, Qualifications And Business Needs, And Without Regard To Race, Color, National Origin, Religion, Sex, Gender Identity, Age, Disability, Alienage Or Citizenship Status, Ancestry, Marital Status, Creed, Genetic Predisposition Or Carrier Status, Sexual Orientation, Veteran Status, Familial Status, Status As A Victim Of Domestic Violence Or Any Other Status Or Characteristic Protected By Applicable Federal, State, Or Local Law.