Senior Analyst/ Analyst- Enterprise SaaS

A. About the Role:

We are looking for a Senior Analyst/ Analyst Enterprise SaaS with strong hands-on experience in Python, Machine Learning, APIs, Databases, and Time-Series Forecasting. The role involves developing data-driven solutions for the power sector, including forecasting, analytics, automation, and ML-based applications.

The ideal candidate should be comfortable working across the complete data science lifecycle from data ingestion and database management to model development, API integration, deployment, and monitoring.

• Develop and maintain Python-based data science and machine learning solutions for power-sector use cases.
• Build forecasting models for power demand, generation, renewable energy, and other operational parameters.
• Perform data cleaning, preprocessing, exploratory analysis, feature engineering, and statistical analysis on large datasets.
• Develop ML models using techniques such as Linear Regression, XGBoost, Random Forest, and deep-learning models such as LSTM/GRU/Transformers.
• Design and implement data pipelines for collecting, transforming, validating, and preparing data for analytics and ML models.
• Work with REST APIs and external data sources to ingest weather, plant, market, and other operational data.
• Design, query, maintain, and optimize relational and/or NoSQL databases used for data science applications.
• Build automated workflows for model training, prediction, data processing, and reporting.
• Analyze model predictions and errors to identify opportunities for improving accuracy and reliability.
• Collaborate with domain experts and engineering/operations teams to understand business requirements and translate them into ML/data solutions.
• Deploy and monitor machine-learning solutions in production environments.
• Maintain documentation for data pipelines, APIs, databases, models, experiments, and workflows.

B. Expectations from the role:

• Strong proficiency in Python, with ability to design and write production-grade code.
• Experience with Machine Learning and Time-Series Forecasting techniques such as XGBoost, LSTM, ARIMA/SARIMA, or similar.
• Hands-on experience with Pandas, NumPy, SciPy, and scikit-learn; TensorFlow/PyTorch is a plus.
• Experience working with REST APIs, databases, and automated data pipelines for data and ML workflows.
• Ability to handle and integrate multi-source datasets, including weather, grid, pricing, and renewable-generation data.
• Strong understanding of data quality, validation, consistency, and timeliness.
• Follow software-engineering best practices including Git, testing, logging, and documentation.

C. Required skill set

• Power Sector Knowledge: Understanding of Indian power-sector operations, data, and IT systems; relevant experience preferred.
• Data Analytics & Visualization: Strong experience in data analysis, visualization, dashboards, and business insights.
• ML Deployment & Inference: Experience developing, deploying, and serving ML models through APIs for real-world applications.
• Python, APIs & Databases: Strong Python skills with hands-on experience in REST APIs, SQL, databases, and data pipelines.

D. Education and Experience

• Education: M.Tech./ BE/ B.Tech (Electrical, Computer Science, IT, Electronics and their associated branches) or M.Sc./ B.Sc. (Computer Science, IT) or MCA.
• Experience: 2–6 years of experience in Data Science, Machine Learning, Forecasting, or Quantitative Analytics roles.
• Domain Experience: Prior experience in Power, Energy, Utilities, Power Trading, or Forecasting is highly desirable.
• Technical Expertise: Strong hands-on experience in Python, Data Analytics & Visualization, ML deployment/inference, APIs, databases, and data pipelines.
• Location
• Base location shall be New Delhi.
• Open to travel for project execution and management.

E. Remuneration Structure

• We offer a motivation based and competitive reward package.