Prescinto
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About
Prescinto is an AI-powered SaaS Asset Performance Management solution for Solar, Wind, and Energy storage. It helps users identify underperformance and its associated losses. The platform provides actionable insights, automated processes, and centralized management, including custom alerts and work order generation. It offers modules for monitoring, analyzing, and operating renewable energy assets, providing near real-time data access, device-level granularity, advanced trend analysis, and AI-powered recommendations. Prescinto's flexible pricing model is based on the MW portfolio onboarded, with volume discounts and billing options. The platform is used by companies across 14+ countries and is trusted by industry leaders.
Platform
Task
Features
• real-time data processing
• performance improvement
• data filtering
• on-ground operation optimization
• improve asset production
• quick, reliable and seamless experience
• centralized asset monitoring
• analyze real-time data - leverage advanced trend analysis - detect underperforming assets - integrated system - automatic work flow management - mttr & mtbf - spare-parts management - mobile
FAQs
What is Prescinto platform?
Prescinto platform is a comprehensive solution for Monitoring, Analyzing, and Operating clean energy assets, including Solar, Wind, and Battery storage systems.
How does Prescinto platform work?
Platform uses advanced analytics and automation to identify and classify defects at the modular level. It also has a custom alert engine that allows users to set custom alerts for their equipment based on varying site conditions, a rule-based analytics model for monitoring field devices and the ability to generate and assign work orders based on alerts automatically.
What types of clean energy assets can Prescinto platform be used for?
Platform can Monitor and Manage Solar, Wind, and Battery storage systems.
What are some of the key features of Prescinto platform?
Some of the key features include advanced analytics, AI-based image processing, custom alerts, rule-based analytics and the ability to automatically generate and assign work orders.
How does Prescinto platform help improve the performance of clean energy assets?
Platform provides asset managers with deeper insights into their systems, allowing them to identify and address issues quickly and efficiently. This results in improved performance and increased generation efficiency.
Job Opportunities
Senior Data Scientist
AI-powered SaaS Asset Performance Management for Solar, Wind, and Energy Storage. Provides monitoring, analysis, and operation tools for improved asset generation and reduced losses.
Benefits:
Strong technical culture of continuous innovation and improvement
Flexible holidays & Insurance for you and your loved ones
Experience Requirements:
6+ years of strong experience in data mining, machine learning and statistical analysis
Experience in productizing models to code in fast paced start-up environment
Other Requirements:
Fluency in tools such as Python, Jupyter Lab / Notebook and libraries such as scikit-learn, pandas, plotly, numpy, keras, etc.
Experience of interfacing with popular frontends and back-end built in Python
Strong intuition for data and keen aptitude on large scale data analysis
Strong communication and collaboration skills
Exposure to clean energy solutions in solar, wind and energy storage would be preferred but is not essential. Exposure to time-series data and analysis would be preferred.
Passionate about a clean energy future
Innovative – you challenge the status quo and find creative solution to problems
Resilient – you enjoy meeting challenges head on and persist till we find a scalable solution
Data driven – you understand the importance of data in decision making
Methodical and team player
Responsibilities:
Research and develop advanced statistical and machine learning models for analysis of large-scale, high-dimensional data.
Dig deeper into data, understand characteristics of data, evaluate alternate models and validate hypothesis through theoretical and empirical approaches.
Productize proven or working models into production quality code
Collaborate with product management, marketing and engineering teams in Business Units to elicit & understand their requirements & challenges and develop potential solutions
Stay current with latest research and technology ideas; share knowledge by clearly articulating results and ideas to key decision makers
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