Data Scientist at Smule
United States of America / Remote

The Smule mission is to connect people all over the world through the joy of making music at massive social scale. Music is much more than just listening… it's about creating, sharing, discovering, participating, and connecting with people. It is a social network with the power to break down barriers, touch souls and bring people together from all over the world.

At Smule, your work will directly impact the product experience of millions of users. You will work collaboratively alongside a team of talented data scientists on cutting-edge projects that have high visibility. You will leverage our datasets that contain demographic, transactional, behavioral, social, text, and audio and video data. We offer a stable, collaborative, and a supportive work environment with a constant stream of new things to learn.

If you have a passion for quality data science and software engineering practices, and enjoy working in a fast-paced, iterative, and a highly rewarding development environment, then Smule is the place for you!

Responsibilities:

  • Build, validate, and deploy machine learning models and recommender systems in batch and real time pipeline
  • Have a customer first approach with a focus on improving user experience by optimizing functional and non-functional parameters such as performance, accessibility, and security.  
  • Write technical specifications, document design approach and all findings, and share with the team
  • Show thought leadership and effectively incorporate machine learning into product features
  • Be a high-performing team player who enjoys collaborating with, learning from, and mentoring other team members to create a positive work environment.
  • Automate data cleaning, transformations, feature engineering, governance, and analysis.
  • Communicate findings clearly and succinctly to technical and non-technical audience.

Requirements

  • 3+ years experience in a data scientist role with a proven track record of deploying machine learning models to production
  • Strong programming skills in Python and Scala and distributed technologies such as Spark, Kafka, and Hadoop
  • Ability to use machine learning frameworks such as scikit-learn, SparkML, or Tensorflow, and tools such as notebooks (Jupyter, Zepellin).
  • Experience with NoSQL and SQL databases, such as Cassandra and Snowflake, respectively.
  • Experience in building and deploying machine learning recommender systems a plus
  • MS/PhD in computer science, mathematics, statistics, or related fields, or equivalent industry experience.