• US Citizen

• Green Card

• Corp-Corp

• Consulting/Contract

• UG :- - Not Required

• PG :- - Not Required

• No of position :- ( 1 )

• Post :- 9th Jun 2022

 

The Client Energy Platform organization is leading Client's efforts to design, develop, deliver and maintain a global energy management platform that unlocks value across Client's Power business. Client Energy Platform aims to enable Client's efforts to harness the potential in its vast fleet of customers, energy assets, and power trading capabilities to deliver value across the energy industry value chain.

 

As a forecasting data scientist intern, you will get to apply your knowledge in statistics, time series analysis, and dynamical systems, work with the latest machine learning models, and build predictive models for energy consumption, energy generation, and energy price, and make an impact by helping Energy Platform clients to make better, safer, more sustainable decisions which yields to cleaner and more sustainable world.

 

WHAT YOU'LL DO:

 

You will work with a team of data engineers and scientists who use data and apply cutting statistical machine learning models to build forecasting models for different energy markets. The entire Data team works collaboratively and is a strong partner for teams across the company. You will get to meet and learn from diverse and talented colleagues. Specific responsibilities include:

 

Analyse energy time series and summarize the statistical properties of energy signals

Build predictive models and forecast signals for day ahead and Realtime market

Evaluate the performance and compare the results with existing models

Deploy the best model and document the result of this research

 

Business Skills

Excellent verbal, written, and interpersonal communication skills

Strong understanding of the product development lifecycles

Strong understanding of software development, testing and integration methodologies

Personal effectiveness/credibility

Strong problem solving and analysis skills

 

 

 

Technical Skills

 

Proficiency with Python or R, SQL and familiarity with working in big data environments

Experience with:

Statistical machine learning tools such as Random Forests, Gradient Boosting, or XGBoost

Time Series Analysis

Deep learning

Model evaluation and hypothesis testing

Deploying apps on AWS cloud infrastructure (i.e., Kubernetes, CICD) is a plus

 

Data sciences experience. 4+ years at least. Forecasting models experience is must have.

AWS experience mandatory. (AWS and Golang good to have not mandatory)

 

Mandatory:

Statistical machine learning tools such as Random Forests, Gradient Boosting, or XGBoost

Time Series Analysis

Deep learning

Model evaluation and hypothesis testing

Deploying apps on AWS cloud infrastructure (i.e., Kubernetes, CICD) is a plus