Data Scientist

Responsibilities
Develop models to improve our ability to find artists, predict cultural trends, and improve artists abilities to acquire fans.
Work with music experts and product owners to identify novel applications for machine learning and data science within our problem space.
Support the development of our MLOps workflow and respective infrastructure to reduce the time from idea to production.
Conduct in-depth analysis of an artists brand, musical style, past releases, and overall fan metrics.
Build action oriented dashboards to track the success of our releases and campaigns.
Support our data analysts in setting up and conducting experiments together with our business.
Support our data engineering team in identifying new data sources and integrating them into our data lake.



Qualifications
3+ years of programming experience with data science focus in Python and SQL. Familiarity with data analysis libraries (e.g. pandas, pyspark) and ML/DL frameworks (e.g scikit-learn, tf/keras) required. Understanding of R and Spark are a plus.
Creative problem solving skills and experience in turning loosely defined problems into machine learning applications.
Balancing statistical rigor to ensure robustness of analysis and models with a focus on delivering value through MVPs and baseline models.
Ability to communicate complex analysis to non-technical audiences, combined with the willingness to become a data science evangelist and increase the overall data literacy within snafu.
The capability to independently identify areas of improvement, combined with the skills to quickly iterate around appropriate solutions are key in a small startup, such as snafu.
Understanding of software engineering best practices (GitOps, OOP) and knowledge of/practical experience with the AWS ecosystem are a plus.
Degree in a STEM field preferred, but not necessary.