About Woodside Energy
We are a global energy company, providing reliable and affordable energy to help people lead better lives. Join our team at Woodside Global Solutions in Bengaluru where talent, digital expertise, and operational excellence converge to solve complex energy challenges, accelerate change, and reimagine business capabilities to support Woodside's global operations and our role in the energy transition.
Founded in 1954, Woodside established the liquefied natural gas (LNG) industry in Australia 40 years ago and supplies customers around the globe. 70 years on, Woodside continues to be driven by a spirit of innovation and determination.
At Woodside, we know great results come from our people feeling valued, getting the support they need to reach their full potential and working in a psychologically and physically safe work environment. We believe in nurturing talent and providing opportunities for continuous learning and career advancement.
Refer to our corporate website for more information about our different locations and projects: What We Do - -Link: What we do - Woodside Energy
About Woodside Global Solutions
Woodside Global Solutions in Bengaluru is being built as a hub of excellence, to drive innovation, digital transformation, and global collaboration.
Working as one Global team, the Woodside Digital team is a trusted partner driving transformation within the organisation. We are bold in our ambitions and resolute in our actions. Through cutting-edge AI, robust cyber security, and advanced data solutions we drive innovation and influence every part of our business.
We are looking for talented professionals who are passionate about technology and eager to make a global impact, helping to shape the future of Woodside together.
About the role
The Data Scientist at Woodside applies domain expertise, scientific acumen, mathematical and statistical proficiency, as well as computing and programming skills to unlock insights from complex datasets and delivering high-impact analytical solutions that enhance decision-making, optimise operations, and unlock value across the oil and gas value chain. The Data Scientist applies their expertise in scientific methodologies, mathematical modelling, statistical analysis, and computational skills to optimize operations and drive strategic initiatives.
The role applies scientific reasoning, statistical modelling, machine learning, and software engineering skills to turn complex datasets into actionable insights.
The Data Scientist will work across diverse business problems—ranging from time-series analytics and anomaly detection to optimisation, simulation, computer vision and applied machine learning—while contributing to the uplift of data science tools, frameworks, and delivery practices.
Duties & Responsibilities:
- Collaborate with business users, internal stakeholders and Digital teams to apply data science techniques to deliver value across the oil and gas value chain, understanding and shape client requirements, and translating them into Data Science actions
- Contribute to data-driven data science project from end-to-end (i.e. problem identification to delivery)
- Evaluate and apply data science concepts and techniques (e.g. predictive modelling, statistical inference, algorithms) to problems in oil and gas exploration and production domains
- Communicate key assumptions, uncertainties, findings of statistical or technical analysis through reports, presentations and translate results back into business language
- Utilizing machine learning, artificial intelligence, and data visualization techniques to identify trends, patterns, and anomalies in oil and gas data.
- Validate models using statistical and scientific methodologies, ensuring robustness, reproducibility, and interpretability.
- Develop predictive models, time-series forecasting methods, anomaly detection pipelines, clustering algorithms, and OCR or neural-network models as required.
- Collaborate with SMEs on analysis and modelling processes to solve challenging and high-impact problems in oil and gas exploration and production domains
- Create documentation, develop and improve data science processes and best practices to ensure the sustainability of work.
- Contribute to successful implementation of solutions, ensuring training and knowledge transfer to stakeholders
- Deliver data science solutions from opportunity identification through to handover, including planning, experimentation, implementation, and monitoring.
Skills & Experience:
- Min. 3-year proven practical experience in Data Science across the end-to-end model development lifecycle, with machine learning and AI methods
- Strong Python programming skills and experience with ML libraries (Pandas, NumPy, SciPy, scikit-learn, PyTorch/TensorFlow).
- Demonstrated expertise in time-series analysis, anomaly detection, clustering, and general applied machine learning.
- Experience developing web applications (Dash, Streamlit) and APIs (Flask, FastAPI, or Django).
- Experience with software engineering best practices (e.g. CI/CD principles under Agile Framework, version control, reproducible research, etc.)
- Desirable experience being part of a multi-disciplinary team for Digital solution delivery or Experience with Cloud Technologies (AWS, MS Azure)
- Tertiary qualification in Computer Science, Statistics, Mathematics, Data Science, Engineering, or a similar quantitative discipline.
- Strong competency using AWS cloud services, including S3, Lambda, SageMaker, containerisation, and serverless execution.
- Strong documentation, communication, and collaboration capabilities.
- Strong problem-solving and critical thinking skills
- Excellent documentation skills to ensure the sustainability of work.
- Quantitative analytics.
- Excellent written and verbal communication
