We are looking for a Data Scientist to join our Data and Insights team. This role will be a critical hire in establishing our Growth practice at Splice and will be relentlessly focused on delivering value to Splice’s users.
In this role, you will devise and refine metrics used to track critical user-centric outcomes. You will use data to identify opportunities to acquire the right users as well as deliver more value to existing users. And you will partner with our Product, Engineering, and Marketing teams to implement experiments that highlight mechanisms to improve these outcomes.
All of this means balancing longer-running data exploration and analysis; conducting experiments; working with Growth and Data Engineers to deliver data products; as well as teaching and enabling Product Managers on the Growth team to obtain and use their own data for ad hoc analysis.
Skills we're looking for
In our opinion, things that can be reasonably expressed in SQL, ought to be. We expect our Data Scientist 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. Our data volume also warrants the ability to write performance-optimized queries.
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 basic statistical inference is required, including tests of significance, sampling and distributions, regression analysis, etc.
As our Growth practice matures, the need for automation will increase. As such, you should have hands-on experience building machine learning models (supervised and unsupervised) and incorporating your models into production workflows, marketing automation, and product experiences. At the outset, this role will largely require a generalist’s skill set; however some degree of specialization in either preference learning and recommendations, text processing and search, segmentation and clustering, or price optimization is desirable.
- 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 query/visualization tools (ideally Looker).
- 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) and normalized, transactional databases (e.g., e-commerce and subscription datasets).
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.