Price Optimization for subscription and usage-based companies
Corrily (Y Combinator W21) helps companies optimize prices and discounts using ML. Our optimizer tests different price points to study their impact on revenue and other downstream metrics. We segment users based on their characteristics such as their location and usage patterns to make sure a director in the US and a student in India aren't offered the same price or discount.
In less than 6 months the company has gone from an idea to a revenue-generating product used by household names in tech including Linktree, IFTTT and Skillshare, among others.
We are now looking to hire a senior data engineer to join a very strong technical team and build together a system that will help power the world's prices.
Infrastructure: GCP fully handled via Terraform (K8s, BigTable, BigQuery, Cloud Run, Cloud Functions)
Databases: BigTable for everything latency-sensitive (we developed a library on top of it to make it easier to use), BigQuery for analytics tasks, Hasura w/ PostgreSQL back-end for configuration / user management
ML: Currently using multiple frameworks (PyTorch for tensor manipulation / legacy neural network models, Nevergrad for non-convex optimization, cvxpy for convex optimization, Pandas and Numpy for data manipulation). The ML stack evolves very quickly as we develop new versions of our optimizer.
Our mono repo is mostly written in Python but we are expecting to expand this in the near future.
Email us at jobs [at] corrily.com
Corrily is building price optimization as a service. Our clients use us to dynamically find the best price and discounts to show their users. A student in a campus in Russia will not have the same willingness and capacity to pay as a senior engineer in San-Francisco, and we believe that showing them the same price is suboptimal. By adjusting prices and discounts, we are able to open up more services to more people. Companies benefit from higher revenues, and a wider audience gains access to otherwise too expensive services. We're made of ex-quants and portfolio manager, both raised in leftist families. We brought this duplicity to the company. We're a weird mix of Marx and Hayek. With both founders being technical, we're very product-focused and fiercely independent. We value people who are self-starters, understand a subject matter, run with it and own the outcome.