Job Description

About Client:


A leading power sector organization.





Roles& Responsibilities:





Responsibilities:

• Analyze large time-series data sets to identify patterns, trends, and anomalies.


• Build, test/validate ML/Deep learning models for time-series data analytics.


• Collaborate with cross-functional teams to understand business requirements and provide data-driven solutions.


• Development and Debugging code.


• Work on global climatic models, meteorological data, plant energy data and plant performance and develop forecasts.


• Apply statistical analysis and hypothesis testing techniques to validate/optimize models.


• Implement iterative development processes to refine/improve data analytics models.


• Stay updated with the latest advancements in time-series data analytics, machine learning, and deep learning techniques.


Experience:

• Data Scientist - 2 - 5 years of proven experience - in building machine learning and deep learning


• Strong proficiency in Python and its data science libraries for time-series data analytics.


• Familiarity with time-series analysis techniques


• Hands on Experience R/Python


• Experience with data preprocessing, feature engineering, and model evaluation for time-series data.


• Proficiency in linear/non-linear modeling, statistical analysis, and hypothesis testing.


• Strong problem-solving skills and the ability to work independently or as part of a team.


• Excellent communication and presentation skills to convey complex concepts to both technical and non-technical stakeholders.


Educational Qualifications:


• Bachelors' degree in computer science / data science / Statistics, or a related field.