Data Scientist - Remote
Company: Sundayy
Location: Location not specified (Remote)
Type: Full-time
Remote: Yes
Posted: 2026-06-03
About this role
About The Company
Phaidra is at the forefront of revolutionizing industrial automation through cutting-edge artificial intelligence solutions. The company is dedicated to transforming static, monolithic infrastructure across various sectors such as manufacturing, power generation, and building management. Traditional facilities often operate on hard-coded control systems that are difficult to adapt and optimize over time, leading to performance degradation and inefficiencies. Phaidra addresses these challenges by developing AI-powered control systems that enable facilities to learn, adapt, and improve autonomously. Leveraging reinforcement learning algorithms, Phaidra converts raw sensor data into actionable decisions, empowering industrial operators with intelligent insights and automation capabilities. The company’s focus on industrial applications ensures utilization of well-sensorized environments with measurable KPIs, making AI integration seamless and impactful. With a team that has a proven track record in applying AI to complex problems—ranging from achieving superhuman performance with DeepMind’s AlphaGo to significantly reducing energy consumption in data centers—Phaidra is committed to delivering innovative solutions that drive operational excellence. Headquartered in the USA and operating as a fully remote organization, Phaidra embraces a global talent pool, hiring internationally through partnerships such as OysterHR. The company's core values—Transparency, Collaboration, Operational Excellence, Ownership, and Empathy—are fundamental to its culture, fostering an environment of trust, continuous learning, and collective success.
About The Role
As a Data Scientist at Phaidra, you will serve as a critical bridge between raw infrastructure telemetry and actionable operational intelligence. Your role involves deep analysis of sensor data from mechanical and electrical systems within data centers and industrial facilities to identify failure sig...