AI Scientist

the business can leverage data and data analytics to drive efficiency, increase customer satisfaction, and develop POCs to solve critical problems for our customers and build state-of-the-art models and deploy them on edge or cloud based systems.

Job Description

The AI Scientist will be responsible for:

• Data cleaning, munging, feature extraction, transformation of structured and unstructured data.

• Design and conduct experiments to develop, test and validate AI/ML models in the context of energy systems and grid automation applications (including model selection, design, tuning, testing, refining, validation, optimization and deployment).

• Identify and integrate new datasets that can be leveraged through our product capabilities.

• Establish test procedures to validate models with real and simulated grid data.

• Responsible for exploratory data analysis (EDA), reporting and visualization of results.

• Applying advance statistical techniques to identify patterns, correlation and trends in the data and derive meaningful insights.

• Create visualization through graphs, dashboards, charts etc. to communicate insights to the leadership and provide platform for Explainable AI.

• Experiment and develop predictive models for Grid applications.

• Develop AI/ML application to build differentiated products and solutions; with ability to work on customers value-driven applications/analytics to drive innovations.

• Develop company A/B testing framework and test model quality.

• Ensure that AI/ML solutions are scalable, efficient, and integrate seamlessly with existing systems and data infrastructure.

• Ensure data adheres to data governance policies and industry standards.

• Collaborate with cross-functional teams of product management, R&D, and other functions, to understand their needs and develop innovative solutions.

QUALIFICATIONS/REQUIREMENTS:

• PhD/Masters'/Bachelors' Degree in Data Science, computer science, electrical engineering, specifically in the computer and electric power engineering field with hands-on experience in data science.

• 2+ years' Experience of working in professional working environment and knowledge of statistical techniques, artificial intelligence (AI) and machine learning (ML), including, unsupervised learning, supervised learning, and reinforcement learning, Deep learning, large language models (LLMs).

• Proven experience in the energy, smart infrastructure, or industrial automation sectors, with deep expertise in system protection, automation, monitoring, and diagnostics, typically acquired through a minimum of 2 years within a multinational manufacturing company.

• Strong knowledge of statistical techniques, model technologies, performance metrics, and validation methodologies for AI/ML models.

• Understanding related to power system protection and automation, monitoring and diagnostics.

• Proficiency in statistical algorithms and machine learning algorithms

• Able to share ideas and work well in a team environment, proactive approach to tasks displaying initiative.

• Flexible and adaptable; open to change and modification of tasks, working in multi-tasking environment.

DESIRED CHARACTERISTICS:

• 2+ years of industry experience
• Ability to simulate using scientific programming tools or languages, such as MATLAB, C++, C, or Python, R, etc.
• Experience with data visualization tools (e.g., Tableau, Power BI, GGPlot etc.).
• Experience in algorithms, libraries (e.g., scikit-learn), machine learning frameworks (e.g. TensorFlow, PyTorch, Scikit-learn), and data processing tools.
• Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
• Understanding and usage of GraphDB, MongoDB, SQL/NoSQL, MS Access, databases.
• Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc.
• Understanding/experience applying data analytics for Electrical Power System or industrial OT system.
• Understanding of GPU Experience, Spark, Scala for distributed computing.
• Strong communication skills and a proactive and open approach to conflict resolution.
• Strong organizational skills, self-motivated, and self-directed.