In 1999, Napster changed the music industry forever when it launched the world's first peer-to-peer music sharing service bringing music online for the first time. Napster revolutionized the way that fans discovered and accessed music by unlocking an unlimited digital jukebox of songs. For 85 million users, Napster was not only their first experience of digital music but also their first real social media experience as they were able to chat with millions of other music fans around the world.
Napster is now the leading independent music streaming service having delivered more than $1BN to artists over the last 20 years. The service offers music fans access to 170M tracks from their favorite artists, music videos, top editorial playlists and new AI and metaverse experiences.
Napster is once again getting ready to revolutionize the music industry, capturing the massive opportunity presented by superfans who want to connect directly with their favorite artists and curators. This will unlock unprecedented new creative and commercial opportunities for the entire music industry and creator economy. Backed by some of the top VC's and Web3 investors, with an industry leading and visionary management team, Napster is perfectly positioned to regain its place as the #1 music platform and pop culture brand.
We are seeking an experienced and passionate Lead Data Scientist to join our growing team. This is a key leadership role where you will leverage your expertise in machine learning, data analysis, and natural language processing to unlock the power of our data and transform it into actionable insights. You will play a pivotal role in building and leading a high-performing team of junior data scientists, guiding them in delivering innovative solutions that improve search, recommendation, and the overall user experience.
Requirements Build and mentor a team of junior data scientists, fostering a collaborative and learning environment. Define the technical vision and roadmap for the data science team, aligning it with overall product goals. Design and develop advanced search algorithms, including user vector-based models and AI-powered search functionalities. Develop and implement machine learning models to personalize user experience, improve content recommendations, and optimize platform performance. Conduct rigorous data analysis to identify trends, understand user behavior, and extract valuable insights. Collaborate with product managers, engineers, and designers to define data requirements and translate business objectives into actionable data science projects. Communicate complex technical concepts to a non-technical audience in a clear and concise manner. Stay up-to-date with the latest advancements in data science, machine learning, and natural language processing, and explore opportunities to integrate new technologies. Develop and maintain strong data pipelines to ensure data quality and accessibility. Champion best practices in data science methodology and documentation. Qualifications
PhD in Computer Science, Statistics, or a related field (or equivalent experience). 5+ years of experience as a Data Scientist or similar role. Proven experience in leading and mentoring a team of data scientists. Strong expertise in machine learning algorithms (classification, regression, recommendation systems, etc.). Experience with natural language processing techniques. Proficiency in data wrangling, cleaning, and manipulation. Excellent communication and collaboration skills. A passion for music and a strong understanding of the music streaming industry (a plus). Experience working remotely and effectively collaborating with globally distributed teams Benefits Competitive salary and benefits package. Opportunity to work on cutting-edge technologies and make a real impact on the future of music streaming. Generous PTO policy including 10 company holidays. Flexible work hours. Work from home with a 100% distributed team. If you are a highly skilled and experienced Lead Data Engineer looking for a challenging and rewarding opportunity, we encourage you to apply.
