Website Royal Dutch Shell
The Energy Platform team is a nimble, cross-functional, deeply technical and passionate group that embodies the speed and agility of a startup while embracing the scale of one of the largest companies in the world. Achieving a balance between agility and global scale provides unique opportunities, and the Energy Platform Team borrows from best-in-class product development, continuous delivery, and commercialization techniques while adapting them to the unique global context within Shell.
The Energy Platform team is empowered to coordinate and align Shell’s energy management platform objectives, strategies, and execution approaches across the company, as well as to design, deliver and maintain a mission critical component of Shell’s ability to deliver differentiated products, offerings and capabilities across its expanding global footprint.
- Builds, on a daily basis, machine learning and deep learning models, optimizing for deployability and scalability of methods.
- Have exceptional skills in statistics and machine learning applied to timeseries analysis (ARIMA, GARCH, BSTS, as well as probabilistic methods for ML/DL)
- Is familiar with applications of distributed compute for ML/DL and has working knowledge of containerized workflows.
- Are comfortable with a fast pace build, test, ship ML/AI workloads into production under a common API.
- Has experience abstracting custom APIs for machine learning methods in training and inference.
- Are eager to work with a cross functional team of energy markets analysts, software developers, ML engineers, to translate business case solutions into new features inside the Energy Platform.
- Have a passion for implementing ML/DL solutions for real-time inferencing over Asset Telemetry data; and is comfortable applying modern Deep Learning techniques to Time Series data.
- Are a maniac for data & model quality, provenance and lifecycle management, supporting an MLOps centric culture within our Data Science and Engineering teams.
- Eager to design, implement and delivery frameworks and workbenches for model building and serving within Energy Platform that enables cross function collaboration.
- Proven history of working with large scale model optimization and hyperparameter tuning, applied to ML/DL models.
Qualification & Experience:
- Must have legal authorization to work in the US on a full-time basis for anyone other than current employer
- Bachelor’s degree in a relevant technical discipline.
- Familiarity with timeseries modeling for financial and electricity market.
- 3+ years of experience with demonstrable proficiency in one or more mainstream opensource Machine Learning/Deep Learning frameworks Tensorflow, Torch, Pyro, Keras, Scikit, Statsmodels.
- Proficiency with Containerized environments and workloads.
- Experience with object-oriented/object function scripting languages Python, R, Go, C++, Scala, etc.
- Excellent analytical, problem-solving, and troubleshooting skills.
- Care deeply about performance, accessibility and API design.
Company: Royal Dutch Shell
Vacancy Type: Full Time
Job Location: Houston, TX, US
Application Deadline: N/A