What you will do
- Work with data scientists, computational scientists, engineers, software developers, and geoscientists across the globe to develop, deliver and apply computational tools, models, or software to support our business
- Use machine learning, pattern recognition, deep learning, statistical analysis and data visualizations – along with domain knowledge and subject-specific models (eg. physics-based) – to solve science, engineering, commercial problems and provide business insights
- Design, build, and execute studies using proprietary or commercial tools to provide insights including calibrating models to field data and providing field optimization recommendations
About You
Skills and Qualifications
Bachelor of Engineering degree and score 70% and above (equivalent CGPA) from a recognized university in one of the following (or similar) disciplines : Chemical Engineering, Mechanical EngineeringMinimum 4 years’ experience in practical development of data science applications including time series analysis, machine learning, and natural language processing in developing, applying, and validating data-driven tools to model complex systemsProficient in the use of python or DataikuIn-depth knowledge and practical experience in applying statistical analysis techniques, such as classification, regression, time-series, Bayesian techniques, etc. and machine learning techniques, such as decision-trees, ensemble methods, deep learning, neural networks, validation methods etcPractical experience in the full machine learning life cycle from problem formulation, data acquisition, modeling building, and deployment at enterprise scale.Specialization in at least one of the sub-domains Natural Language Processing (NLP), Computer Vision, Time series forecasting, PINN’s, causality analysisExperience in Python & R and related packages such as numpy, pandas, sklearn, Keras, Tensorflow, PyTorchExperience with software engineering practices, agile methodologies, DevOps, version controlExperience working in Azure Databricks or any other data science frameworksSoftware testing and development practices (Agile)Preferred Qualifications / Experience :
Knowledge of supply chain operations including demand planning, inventory optimization, vehicle routing, network optimization is an advantageExperience in developing, applying, and analyzing physics-based and / or data driven computational models and simulations is an advantagePrior knowledge of commercial software development and / or experience in commercial software teamsExperience of identifying and scoping data science opportunities based on business needs is an advantageStrong communication and interpersonal skillsYour benefits
An ExxonMobil career is one designed to last. Our commitment to you runs deep : our employees grow personally and professionally, with benefits built on our core categories of health, security, finance and life. We offer you :
Competitive compensation
Medical plans, maternity leave and benefits, life, accidental death and dismemberment benefits
Retirement benefits
Global networking & cross-functional opportunities
Annual vacations & holidays
Day care assistance program
Training and development program
Tuition assistance program
Workplace flexibility policy
Relocation program
Transportation facility
Please note benefits may change from time to time without notice, subject to applicable laws. The benefits programs are based on the Company’s eligibility guidelines.
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