[Remote] Senior Data Scientist (Power Systems) at Phaidra

Remote

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Industrial Automation, Artificial IntelligenceIndustries

Requirements

Experience with reinforcement learning algorithms
Knowledge of industrial applications and sensor data
Ability to configure AI control systems without writing code
Understanding of AI and its applications in production
Experience with machine learning and statistical methods
Familiarity with electrical system ontology and data center electrical systems
Ability to work with multiple systems (electrical, mechanical, environmental)
Strong analytical and problem-solving skills
Experience with root cause analysis and anomaly detection
Ability to collaborate with customer operations teams

Responsibilities

Develop electrical system ontology for data centers
Create and utilize tools to monitor system telemetry
Develop and deploy advanced anomaly detection models
Design automated alerting frameworks
Perform root cause analysis on anomalies and power incidents
Collaborate with customer operations teams to translate anomaly insights into actionable strategies
Grow the knowledge base about data center electrical systems within Phaidra

Skills

Key technologies and capabilities for this role

Reinforcement LearningAIData ScienceSensor Data AnalysisMachine LearningDeepMindGoogle Data Centers

Questions & Answers

Common questions about this position

Is this a remote position?

Yes, Phaidra is 100% remote with no physical office, and they hire employees internationally across multiple countries including the USA, Canada, UK, and others.

What are Phaidra's core values?

Phaidra's core values are Transparency, Collaboration, Operational Excellence, Ownership, and Empathy, which they seek in individuals to deliver excellence and foster a supportive culture.

What skills are required for the Senior Data Scientist role?

The role requires expertise in developing electrical system ontologies for data centers, working with AI and LLMs, and creating tools to monitor system telemetry from sensors, smart meters, and facility management systems.

What should I include in my application?

Submit your resume/CV, and optionally a cover letter explaining your ideal position and how your skills fit with the team.

What is the salary for this position?

This information is not specified in the job description.

Phaidra

AI virtual plant operators for industrial efficiency

About Phaidra

Phaidra deploys artificial intelligence virtual plant operators to support operations teams in critical facilities. Their AI-powered control systems are designed to enhance stability, energy efficiency, and sustainability by learning and adapting over time. Unlike traditional static control systems that cannot adjust dynamically, Phaidra's technology continuously improves performance, addressing issues of degradation and lack of resiliency in industrial settings. The company has achieved notable success, such as delivering 40% energy savings at Google's data centers, and is expanding its solutions to various sectors, including pharmaceutical production and data centers. Phaidra's goal is to enhance operational efficiency and sustainability for its clients, generating revenue through the implementation and maintenance of its AI-driven systems.

Seattle, WashingtonHeadquarters

2019Year Founded

$41.3MTotal Funding

EARLY_VCCompany Stage

Industrial & Manufacturing, Energy, AI & Machine LearningIndustries

51-200Employees

Benefits

Health Insurance

Dental Insurance

Vision Insurance

Unlimited Paid Time Off

Parental Leave

Home Office Stipend

Company Equity

Risks

Increased competition from AI-driven industrial solutions providers could impact Phaidra's market share.

Rapid AI advancements may require Phaidra to continuously innovate, straining resources.

Potential data privacy concerns and regulatory scrutiny could challenge Phaidra's operations.

Differentiation

Phaidra offers AI solutions for mission-critical facilities, enhancing stability and efficiency.

The company combines AI expertise from Google-Deepmind with industry knowledge from Trane and Johnson Controls.

Phaidra's AI systems adapt and improve over time, unlike static, hard-coded control systems.

Upsides

Phaidra achieved 40% energy savings at Google's data centers, showcasing its effectiveness.

The rise of edge computing complements Phaidra's solutions for real-time analytics and efficiency.

Growing interest in AI-driven predictive maintenance aligns with Phaidra's focus on stability.

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