• Hands on experience to work on time series modelling, time series prediction and forecast algorithms

• Apply various conventional AI/ML algorithms such as ARIMA, SARIMA and deep ML based algorithms such as LSTM, RNN, Auto encoders

• Apply state-of-the-art AI/ML algorithms such as Linear regression, Na ve Bayes, Decision Trees, Random Forest, SVM, PCA, PLS etc.

• Apply probabilistic forecast on time series data

• Work on problems related to predictive maintenance, asset health monitoring, Residual Useful Life (RUL) calculation etc.

• Apply statistical signal processing techniques for data cleaning

• Apply time series techniques like Fourier transform, Fast Fourier transforms, Wavelets to solve problems related to time series analysis

• Analyze time series data using correlation analysis, partial correlation analysis, factor analysis, contribution plots

• Estimate model orders, delays from the data, refine models based on performance metrics

• Build pipeline of AI/ML using data pre-processing, feature engineering, modelling, post processing, result validation, model deployment

• Ability to work on large scale time series data

Qualifications: Education, Competencies (Knowledge, Skills Behaviour) and Experience

• Minimum Qualifications

• PhD, M.E/ M. Tech, B Tech in Computer Science (preferred), Electrical Engineering, Mathematics, Statistics any other related discipline

• PhD+5 years or Master+8 years, B.Tech. +12 years of solid experience in Industry or academia.

• Experience in programming languages like R, Python, PySpark, MATLAB etc.

• High quality organizational and leadership skills

• Ability to study state of the art of research publications and patents

• Outstanding communication (verbal, written) and presentation abilities

• Positive team player attitude with conflict management and influencing skills.

• Experience mentoring team members and/or leading teams

• Preferred Qualifications

• Exposure or knowledge in Renewable Tech companies

• Hands-on experience in Big data tools like Apache Spark, Kafka, Pulsar, HDFS, Apache Airflow, Cassandra, MongoDB, Elasticsearch, time-series databases etc.

• Exposure to machine vision and deep-ML architectures such as CNN, R-CNN, Fast CNN, Faster R-CNN, YOLO, Detectron etc.

• Experience of publishing patents and publications