Sr Data Scientist Marketplace And Merchandising at Splice

About the role
We are looking for a Sr. Data Scientist to work with our Content, Merchandising, and Product teams to optimize the content in our Sounds & Gear marketplaces. In this role, you will define metrics that track engagement and user-centric outcomes in our marketplaces. You will help us understand what content is most valuable to drive engagement. Working in close partnership with Product, Design, and User Research, you will use analytics to discover patterns of user behavior and leverage these discoveries to build more relevant and impactful experiences for our users.
All of this means balancing ad hoc data exploration and longer-running analytical projects; designing and conducting experiments; bridging the gap between Product Managers and Data Engineers to assure that the necessary data is accessible and easy to use; aiding in the design of Product roadmaps to support our marketplaces; and building models that drive in-product experiences—e.g., personalized merchandising.
What we're looking for:
Data manipulation
We expect our Data Scientists to have strong analytical SQL skills. This means fluidity constructing statements that rely on a combination of joins, aggregate functions, subqueries, and window functions. This role will work with large-scale data, so this person must have experience writing efficient, performance-optimized queries.
Analysis
Nearly every problem starts with models that can be interpreted to drive human action. We’re seeking an individual who enjoys experimentation and statistical analysis—someone who can translate what they see in the data into useful suggestions. A thorough understanding of statistical inference is required.
Modeling
You should have hands-on experience building machine learning models (supervised and unsupervised) and know how to incorporate your models into production workflows and product experiences. 
Tooling expectations:

Regular usage of a programming language typically used for statistical analysis and machine learning (ideally Python). Familiarity with a statically typed language (ideally Java or Scala) is desirable.
Strong experience with analytical SQL (ideally BigQuery, Snowflake, AWS Athena, or similar).
Exposure to large-scale model training in a platform like Spark is desired.

Hands-on experience with self-service product-analytics tools (e.g., Looker, Mixpanel, Amplitude, Heap).

Training in statistics, econometrics, or machine learning, with plenty of real-world experience applying these methodologies.

Exposure to a variety of data sets used by Product teams. Chiefly, large-scale event data (e.g., Mixpanel, Segment, Snowplow, server logs) and normalized transactional databases (e.g., e-commerce and subscription datasets).


Additional:
There are no specific degree requirements for this role: we appreciate and seek out diverse backgrounds. Instead of any particular formal education requirement, we’ll flesh out what you’ve built, what you know, and how you approach problem solving.
As a company that serves musicians and producers, some knowledge of the music-production process is an asset. If this topic is new to you, that’s okay—you should be open to learning about it.
Equal Opportunity Employer:
Splice is an equal opportunity employer, committed to diversity and inclusion. We will consider all qualified applicants without regard to race, color, nationality, gender, gender identity or expression, sexual orientation, religion, disability or age.