Data Scientist at Recurrency

Recurrency is building the automated enterprise. Our product is the world's first enterprise optimization system (EOS), a machine learning application that integrates with legacy enterprise resource planners (ERP) like SAP, Oracle, Microsoft Dynamics, or Epicor, and provides the user with the flows and recommendations on how to better buy, manage, price, and sell their inventory. Our customers are wholesalers and distributors, ranging from family-owned companies to the Fortune 500. 
Despite being a multi-trillion dollar industry, wholesale distribution has a striking lack of software to support even basic operations, with most ERPs relying on decades-old architecture. Founded in Los Angeles and supporting a fully-remote team across the US, we are a well-funded Series A-stage startup, backed by some of the most successful VCs in the world.

As a Data Scientist, you will leverage existing knowledge in Machine Learning and Big Data to build and deploy the models that drive key business insight for our customers. As one of the founding members of our team, you'll be engineering the next-generation data science features for the world-wide supply chain. Our team does it all - and you will be a core contributor - designing, testing, and deploying a system of bleeding edge Machine Learning models, preparing data and engineering features, tracking metrics, maintaining the health of our code, and continually growing as an engineer and researcher. The ideal candidate is both forward-thinking and hands-on, has a strong sense of ownership and drive for delivery, and is a good mentor and co-worker. At Recurrency, we pride ourselves on the collaboration between Product, Design, and Engineering and so you have the opportunity to be involved in the entire product lifecycle, from ideation through building, deploying, and continual improvement and evolution.


What you will own:

Develop forecasting, recommendation, and pricing models to improve the quality of wholesale distribution systems.
Feature engineering and data pipeline design.
Metrics building and monitoring.
Work with our Engineers and Product team to build and improve efficient data products.



What you will bring on Day 1:

MS or PhD in Data Science, Computer Science, Math or related field.
3+ years research experience in Machine Learning.
Knowledge in forecasting, recommendation, or pricing is a plus.
1+ years in a Data Science, Machine Learning or related role. 
Fluency in Python and PyTorch.
Previous experience with databases (Postgres or MongoDB) and Cloud technology stacks (AWS, etc).
Foundation in data structures, algorithms, and software design with strong analytical and debugging skills.
Strong interpersonal, communication, and collaboration skills with great problem solving abilities.
A desire to be part of a diverse and growing team.



Nice-to-haves, which we're sure you'll pick up along the way:

Experience with Docker, Airflow, ECS


#LI-Remote



Recurrency is a fully-remote team, with team members located throughout the US. While it will never be a requirement, there is a high likelihood that we will eventually develop a bi-coastal office presence, centered around Los Angeles & NYC, for those who prefer in-person to remote work.

Recurrency celebrates and embraces diversity and is committed to building a team that represents a variety of experiences, backgrounds, and skills. We do not discriminate on the basis of race, color, religion, marital status, age, gender identity, gender expression, sexual orientation, non-disqualifying physical or mental disability, national origin, veteran status, or other applicable legally protected characteristics.