Join Spotify as a remote Live Chat Support Data Scientist for the Customer Service Platform. Utilize your expertise to enhance user experiences. Analyze customer interactions, extract insights, and optimize support strategies. Collaborate across teams to drive efficiency and satisfaction, ensuring seamless music streaming. Shape the future of customer support in the dynamic realm of music and technology.
Key Skills
Java Programming, Python Programming, C++, C Programming, SQL, Apache Hadoop, Scala Programming, Machine learning techniques, Data science techniques, PyTorch, TensorFlow, MapReduce, R Programming
Job Description
The Freemium R&D team oversees the entire user journey on Spotify and ensures we engage with people in innovative ways, every step of the way. Our team grows Spotify’s audience by finding future listeners around the world and delivering the right value to them, at the right time. With research, product development, product design, engineering, and marketing all collaborating in one organization, we’re able to quickly create meaningful features and services for millions of people around the world, resulting in joyful, long-lasting relationships with Spotify.
Location: London or Remote EMEA
Job type: Permanent
Spotify is diversifying: audiobooks, artist merchandise, podcast advertising and many other areas. Each of these services requires a customer service experience that gives users the help they need when they need it. Which is where this team comes in!
As a Product Insights Data Scientist working on the customer service platform, you will be building insights from the ground up as we reinvent how we serve our users’ customer service needs. From scoping data and building out ETLs with Data Engineers, to delivering insights that advise the product roadmap for our many customer service tools (such as chatbots, FAQs, agents, multichannel optimization and more)! Sound exciting?
What You’ll Do
• Drive prioritisation by estimating the impact of potential product changes, and creating frameworks to align interested parties. • Define metric frameworks and partner with engineering to instrument our product. Building systems and practices that allow us to monitor progress at scale efficiently. • Partner with product managers, user researchers and design to create & communicate insights that directly drive major product decisions. • Identify the most suitable insights methods (exploratory data analysis, experimentation, causal inference, regression methods, ML etc) to support all stages of the product development cycle (from conceptualisation to shipping/optimisation). • Partner with user researchers to combine qualitative and quantitative insights into more powerful and compelling stories – understanding the what and the why.
Who You Are
• 3+ years of professional experience in data science or related fields. • A technically minded data scientist with a deep understanding of data, instrumentation, and pipelines. • Previous experience partnering with engineering to deliver metrics frameworks & dashboards. • Ability to query large datasets with SQL (our DWH is in BigQuery) along with great coding skills (Python or R). • You have great knowledge of analytics & visualisation libraries (e.g. pandas, tidyverse, seaborn, ggplot), and visualisation tools (Looker or similar) with a proven record of appealing visuals. • Ability to use statistics to drive business decisions. Methods include: success metrics, a/b testing, determining statistical significance and presenting findings with clear product recommendations or implications.
Where You’ll Be
• We are a distributed workforce enabling our band members to find a work mode that is best for them! • Where in the world? For this role, it can be within the EMEAregion in which we have a work location • Prefer an office to work from home instead? Not a problem! We have plenty of options for your working preferences. Find more information about our Work From Anywhere options here. • Working hours? We operate within the Central European time zone for collaboration • We ask that our team members be located within Greenwich Mean time zone, Central European time zone, or Eastern European standard time zone for the purposes of our collaboration hours Our global benefits Extensive learning opportunities, through our dedicated team, Green House. Flexible share incentives letting you choose how you share in our success. If you think this role describes you, we would love to hear from you. Apply now to join our team!
