Senior Data Scientist

Key Skills

Python Programming, SQL, Cloud computing

Job Description

The Senior data scientist will join the newly created Data Science and ML Capability Center (DSML CC) within the Information, Data and Analytics (IDA) team/IT Digital Engineering VPship. The CCship is responsible for delivering Machine Learning and Data science solutions to all Shell Businesses – UP, IG, Downstream, C&P, RES.

The Senior Data scientist will be responsible for initiating, development and deployment of large scale data science solutions/products in an agile fashion to the Shell businesses. They will also be accountable for adhering to Shell quality standards for producing digital solutions.

The position is with the Subsurface and Wells team in DSML CC, which focuses on digital solutions for the exploration, subsurface and wells management and development.

Responsibilities

• Accountable for delivery of data science products in a production scale environment.
• Managing the product lifecycle especially relating to data science, development to support.
• Transformation of proof of concepts into a larger deployable product in Shell. Rinse and repeat, cross-pollinate ideas across projects and assets.
• Partnering with P&T research teams, to convert proof of concepts into scalable data products.
• Value estimation and realization, end-to-end value mapping for assets thru data science solutions.
• Supervision and contribution to project work to build machine learning models and digital solutions, providing the technical assurance on end-2-end delivery of data science solutions for the Shell businesses, in particular the machine learning component.
• Adhering to the principles of delivering quality through the MCDS digital quality initiative by conducting regular health checks, audits, code reviews to ensure that clean and maintainable production-level code is being produced by project teams.
• Evaluation and benchmarking of all new asset related initiatives prior to developing solutions.
• Keeping abreast of new engineering practices, technologies and continuously improving our Agile practices and building and strengthening relationships and alliances in academia, IDT and industry.

Required Skills and Experience

• Master’s degree in any of the following: mathematics, statistics, econometrics, machine learning, or relevant subsurface disciplines, e.g. petrophysics, geology, reservoir engineering, etc.
• Active experience in at least one of the subsurface disciplines, e.g. geophysics, petrophysics, geology, reservoir engineering, etc.
• At least five-year experience in developing end-to-end models using machine learning for predictive modelling in a business/industry environment, i.e. feature engineering, model creation and evaluation.
• Experience in developing, deploying, supporting models in production.
• Proven ability to write clean, elegant and maintainable production-level code in Python and R, and experience in version control, testing, refactoring.
• Experienced coder in data science languages such as R and Python (Pandas, Scikit Learn, etc.).
• Firm grasp and demonstratable experience on the principles of the model development lifecycle and producing machine learning models that stand up to statistical rigor.
• Good knowledge and understanding of Shell.ai, GIT, Azure, CI/CD pipelines.
• Experience in Agile working methodology.
• Coaching capability for more junior team members.
• Strong communication skills, especially explaining technical concepts to business stakeholders.
• Extensive experience working in small, empowered, delivery focused, cross-functional and collaborating teams.
• Experience of working in a virtual team and with virtual stakeholders.

Have experience in at least one out of the following:

• Probabilistic Modelling (e.g. General Linear Models, Stochastic Processes, Bayesian Networks, Hidden Markov Models, Hierarchical Modelling, Time Series Modelling, etc.);
• Algorithms and optimization (e.g. linear programming, multi-objective optimization, meta-heuristics, etc.);
• Knowledge of Bayesian Statistics and Bayesian/Probabilistic modelling.

Desired Skills and Experience

• Knowledgeable in at least one of the following topics: Computer Vision, Deep Learning, NLP and reinforcement learning.
• Experience working with one of the big cloud environments (e.g. AWS, Azure, GCP, etc.).
• Independent analytical thinker - ability to challenge established thinking to stimulate creativity.
• Experience in identifying and performing initial scoping of data science opportunities with the business.

This job profile contains generic information and does not describe individual positions or required job competencies. Grading decisions will also depend on other factors.

There is a preferred candidate identified for this position.