About the Role

We are looking for a Data Scientist to join our Data and Insights team. In this role, you will define metrics used to track engagement, feature usage, and user-centric outcomes. You will use data to uncover user preferences and quantify product experiences, all with an aim of guiding our Search and Recommendations team 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; regularly presenting findings to the Data and Insights team, Search and Recommendations team, as well as the company.

Skills we're looking for

Data manipulation

In our opinion, things that can be reasonably expressed in SQL, ought to be. We expect our Data Scientists to have strong analytical SQL skills. This means a 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

Right now, our bias is toward 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 policy 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. At the outset, this role will largely focus on experimentation and more foundational product analysis; however, some degree of specialization in either preference learning and recommendations or text processing and search is expected.

Tooling expectations

• Regular usage of a programming language typically used for statistical analysis and machine learning (ideally Python). 
• Strong experience with analytical SQL (ideally BigQuery, Snowflake, or a similar MPP data-warehouse technology).
• 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 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 comments

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.