CA and US only
About the Client
Our client is at the forefront of enhancing data reliability across industries, pioneering the sector's inaugural end-to-end Data Observability platform. Their mission is critical in today's digital landscape—ensuring the accuracy and dependability of data that powers digital products and informs decision-making. Recognized for their innovation and workplace culture, including being named an Enterprise Tech 30 company and receiving accolades from Forbes, Inc., and others, they have garnered significant investment to drive their mission forward. They partner with leading companies to foster trust in data, reflecting a commitment to diversity, inclusivity, and creating a global team that mirrors the vast array of human experience.
About the Role
The client seeks a Data Scientist passionate about building and deploying Machine Learning capabilities from the ground up. This role offers the chance to take considerable ownership within a dynamic startup environment, collaborating closely with a team of skilled data scientists and engineers. The position is open to candidates across the US, emphasizing a remote work culture that values inclusivity and diversity.
What You'll Do:
Develop and deploy production-grade ML algorithms.
Lead ML projects from the conceptual stage to operational deployment.
Tackle complex problems in anomaly detection and prediction.
We're Excited About You Because:
You have at least 3 years of experience in bringing ML algorithms to production.
You possess strong skills in Python and SQL.
You exhibit a strong sense of urgency, an ownership mindset, and an intuitive grasp of product development.
You have expertise in time-series analysis, anomaly detection, and unsupervised learning methods (preferred).
Why Join?
Joining this team means contributing to a culture that values equality, inclusivity, and diversity. Our client is dedicated to building a global team that brings a wide range of backgrounds, perspectives, and experiences to the forefront, driving innovation and trust in data across enterprises. This is an opportunity to impact significantly in a rapidly growing field, supported by a world-class employee experience and a commitment to an inclusive work environment for all.
United States
