Data Scientist (Energy Sector)

WorkOnGrid; Bengaluru; On-site; INR 1,000,000 - 1,500,000; Full time

Job summary

WorkOnGrid in Bengaluru is seeking a passionate Data Scientist to leverage data science techniques in the energy sector. You will collaborate with stakeholders to develop solutions for energy demand forecasting and smart grid optimization.

The ideal candidate has 3-5 years of experience and a Master's in Data Science. Proficiency in Python and experience with tools like TensorFlow and SQL are essential. This role contributes directly to AI-driven transformations in the energy industry.

Qualifications

• 3-5 years of experience as a Data Scientist in the energy sector.
• Strong programming skills in Python, hands-on with various libraries.
• Proficient in SQL and data querying.

Responsibilities

• Collaborate with teams to understand energy sector challenges.
• Design machine learning models for energy applications.
• Prepare data from diverse sources for analysis.

Skills

Python programming

Machine Learning

Data Visualization

Statistical Analysis

SQL

Education

Master's in Data Science or related field

Tools

TensorFlow

PyTorch

Tableau

Hadoop

Job description

We are looking for a passionate Data Scientist with 3-5 years of experience in the energy sector to join our team. In this role, you will leverage advanced data science, machine learning, and deep learning techniques to solve real-world challenges in energy demand forecasting, smart grid optimization, renewable integration, and asset performance. You will work closely with business stakeholders, domain experts, and data engineers to turn complex datasets into actionable insights that drive efficiency, sustainability, and innovation in the energy industry. This role offers the opportunity to contribute directly to the transformation of the energy sector through AI-driven solutions.

Responsibilities

• Collaborate with business stakeholders and domain experts to understand challenges and opportunities within the energy sector.
• Design and develop machine learning and deep learning models for energy applications such as demand forecasting, grid management, renewable integration, and equipment optimization.
• Acquire and prepare data from diverse sources (IoT sensors, smart meters, SCADA systems, weather data, and market prices), ensuring quality and readiness for analysis.
• Conduct EDA to identify patterns, correlations, and anomalies that drive actionable insights.
• Implement data science solutions using regression, classification, clustering, and neural networks to improve decision-making and operational efficiency.
• Evaluate model performance with appropriate metrics and continuously refine models for accuracy and reliability.
• Develop clear dashboards, reports, and data visualizations to communicate findings to technical and non-technical stakeholders.
• Stay updated with emerging trends in AI, IoT, renewable energy technologies, and energy analytics.
• Collaborate with Data Engineers to enhance data infrastructure, collection strategies, and model deployment processes.
• Provide technical guidance and mentor junior data scientists or analysts when required.

Requirements

• Master's in Data Science, Computer Science, Engineering, or a related quantitative field.
• 3-5 years of experience as a Data Scientist, with a focus on the energy/utilities/renewables domain.
• Strong programming skills in Python, with hands-on experience using pandas, scikit-learn, TensorFlow, PyTorch, or Keras.
• Proficiency in SQL for data querying and transformation.
• Strong foundation in machine learning algorithms, statistical analysis, and deep learning frameworks.
• Experience with data visualization tools (Tableau, Power BI, etc.)
• Familiarity with big data technologies (Hadoop, Apache Spark, Databricks) and cloud platforms (AWS, Azure, GCP).
• Domain expertise in areas like renewable energy, power generation, smart grids, oil and gas exploration, or energy trading.
• Strong analytical, problem-solving, and critical‑thinking skills with experience working on large, complex datasets.
• Excellent written and verbal communication skills.