Data Scientist - Music Mission

The Music Mission enables Music creators to grow, engage & monetize their fan bases on Spotify. Central to the Music Mission's vision is the development of promotional tools for artist and label teams, powered by Spotify's deep knowledge of listener behavior. Products like Discovery Mode, Marquee, Showcase, Music Videos and Clips enable artists and their teams to grow, monetize and connect with their audience. We're looking for a Data Scientist to join Discovery Mode, part of the Music Mission. Discovery Mode helps artists and music marketers reach new listeners when it matters most. Artists and labels flag priority songs, and our system feeds that signal into the algorithms behind personalized playlists. In this role, you'll partner with product, engineering, and user research to build the technology that powers Discovery Mode. Your focus will be customer engagement and reporting — understanding what customers need, building instrumentation and dashboards for our self-serve product, and running experiments that improve the experience and drive business impact. As part of the Product Insights team, you'll help define the next generation of promotion products for the music industry. What You’ll Do Work closely with cross-functional teams of data scientists, researchers, product owners, engineers, designers, marketers, and others across the company to develop the next generation of promotion tools for artists. Identify the most impactful opportunities for product development based on user needs, and execute on them diligently and resourcefully. Define metrics and build the dashboards we use to measure the health and success of our products. Partner closely with other data scientists to inform, build and test hypotheses that deliver actionable insights to improve and expand our products. Contribute to a community of data scientists by evolving best practices and learning new skills. Maintain a culture of rigor an

We are seeking Research Scientists (across all levels of seniority) to join our Artist-First AI Music Lab. Our team pioneers and advances state-of-the-art generative technologies for music that create breakthrough experiences for fans and artists. We invent entirely new listening experiences that center and celebrate artists and creatives. All of our products will put artists and songwriters first, through these four principles: Partnerships with record labels, distributors, and music publishers: We’ll develop new products for artists and fans through upfront agreements, not by asking for forgiveness later. Choice in participation: We recognize there’s a wide range of views on the use of generative music tools within the artistic community. Therefore, artists and rightsholders will choose if and how to participate to ensure the use of AI tools aligns with the values of the people behind the music. Fair compensation and new revenue: We will build products that create wholly new revenue streams for rightsholders, artists, and songwriters, ensuring they are properly compensated for the use of their work and transparently credited for their contributions. Artist-fan connection: AI tools we develop will not replace human artistry. They will give artists new ways to be creative and connect with fans. We will leverage our role as the place where more than 700 million people already come to listen to music every month to ensure that generative AI deepens artist-fan connections. Learn more in our press release: https://newsroom.spotify.com/2025-10-16/artist-first-ai-music-spotify-collaboration/ What You'll Do Conduct groundbreaking research in generative audio using diffusion or flow matching models, with a focus on one or more of the following areas: Vocal Synthesis — Research in vocal and speech synthesis, along with related areas such as ML-based audio processing and signal processing.

The Personalization team makes deciding what to play next easier and more enjoyable for every listener. From Blend to Discover Weekly, we’re behind some of Spotify’s most-loved features. We built them by understanding the world of music and podcasts better than anyone else. Join us and you’ll keep millions of users listening by making great recommendations to each and every one of them.Spotify’s Personalization organization builds the technology that helps millions of listeners discover what they love. Within this space, our research team focuses on advancing the state of the art in machine learning and AI to shape the future of personalization. We explore new approaches, challenge existing assumptions, and contribute to the broader research community while influencing long-term product direction. What You'll Do Conduct original research in machine learning and AI, with a focus on large-scale foundation models, generative AI, and post-training methods, including reinforcement learning. Develop novel methodologies, models, and evaluation frameworks to advance personalization systems. Design and execute rigorous experiments to explore new ideas and validate research hypotheses. Contribute to the scientific community through publications, talks, and conference participation. Collaborate with cross-functional partners to translate research insights into long-term product opportunities. Help define and evolve a forward-looking research agenda aligned with Spotify’s personalization strategy. Mentor others and contribute to a strong, curious, and collaborative research culture. Who You Are You have a Master’s or PhD in machine learning, AI, or a related field, or equivalent research experience. You have demonstrated expertise in machine learning and artificial intelligence through peer-reviewed publications at conferences such as NeurIPS, ICLR, ICML, KDD, or RecSys. <

The Personalization team makes deciding what to play next easier and more enjoyable for every listener. From Blend to Discover Weekly, we're behind some of Spotify's most-loved features. We built them by understanding the world of music and podcasts better than anyone else. Join us and you'll keep millions of users listening by making great recommendations to each and every one of them. Within Personalization, the Speak Team owns the development of Spotify's state-of-the-art speech models, contributing to speech recognition, speech synthesis, and speech-to-speech models. We craft voice models that match human-level emotional expressiveness, so we can deeply engage our listeners and support creators at scale. Our groundbreaking work on speech synthesis relies on state-of-the-art deep learning methods and evaluation techniques, highly efficient data processing and model serving, and capturing audio of outstanding quality from our voice talent pool. We're looking for a senior applied research scientist with experience in developing novel ML techniques and architectures and with a strong interest in working across a full production pipeline to produce state-of-the-art generative conversational speech-to-speech models. You'll collaborate with our engineering teams to help develop our production pipelines, explore new ideas and methods to improve quality, understanding and realism, as well as push the frontiers of what is possible with our speech technology. What You'll Do Develop and experiment with new methods for speech synthesis and speech recognition, along with end-to-end approaches, building on the latest research and ideas. Work towards the expansion of our speech use-cases targeting different markets and products. Be part of a highly motivated research team dedicated to building and creating models at scale to power the Spotify platform. Champion best practices for research and development, sharing your knowledge and exper

The Personalization team makes deciding what to play next easier and more enjoyable for every listener. From Blend to Discover Weekly, we’re behind some of Spotify’s most-loved features. We built them by understanding the world of music and podcasts better than anyone else. Join us and you’ll keep millions of users listening by making great recommendations to each and every one of them. The Surfaces Podcasts team owns podcast recommendations across some of Spotify’s most visible surfaces, including Home and the Now Playing view. We build and improve the recommendation systems that help listeners discover their next favorite show or episode while helping creators reach the right audiences. As a Staff Machine Learning Engineer, you’ll help shape the future of personalized discovery and engagement at Spotify. You’ll work at the intersection of recommendation systems, large language models, and production-scale machine learning infrastructure to build experiences for listeners at global scale. You’ll take models from research to production, help set technical direction in ambiguous problem spaces, and solve complex personalization challenges across Spotify. What You'll Do Own and improve the machine learning models and systems that power the Home feed, including the Shortcuts experience. Design, build, and ship personalized recommendations that serve millions of Spotify listeners globally. Build content recommendation systems for emerging agentic and AI-powered user experiences. Train, fine-tune, evaluate, and optimize large language models using techniques such as supervised fine-tuning (SFT), distillation, and parameter-efficient training approaches. Partner closely with Product Managers, Engineers, Data Scientists, and Designers to define and execute experimentation strategies. Drive A/B testing, monitoring, model evaluation, and continuous optimization of recommendation quality, reliability, and cost efficiency.

About Ramp Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $200B in annualized spend flows in and out of 70,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. About the Role We’re looking for someone to help lead the future of analytics at Ramp. This person will enable Ramp to get 1% better every day by developing data products and insights. They will partner closely with business stakeholders and product, engineering, and design counterparts to prioritize and execute on work, improve reporting, as well as drive results and process improvements. What You’ll Do Full stack development, building models to consume, transform, and expose data to stakeholders and production systems Drive a culture of experimental design, testing agenda, and best practices Contribute to the culture of Ramp’s data team by influencing processes, tools, and systems that will allow us to make better decisions in a scalable way Collaborate with P/E/D/D (product, engineering, data and design) teams to develop product roadmaps and measure success Work closely with data engineering teams to capture, move, store, and transform raw data into highly actionable insights, and partner with business teams to turn those insights into action Wha