Deskripsi Pekerjaan
Are you an expert in quantitative analysis looking to solve complex global energy challenges? ExxonMobil is seeking a highly analytical Data Scientist specialized in Time Series Forecasting to join our world-class team in Kuala Lumpur. In this role, you will leverage massive datasets to build predictive models that optimize operational efficiency and inform critical decision-making processes across our global infrastructure.
You will work at the intersection of advanced statistics, machine learning, and domain expertise. This is an opportunity to apply rigorous academic methodologies to real-world industrial problems, utilizing state-of-the-art computational resources to drive innovation in forecasting accuracy and supply chain optimization.
Tanggung Jawab
- Develop and deploy advanced time series forecasting models to predict demand, supply, and equipment reliability.
- Collaborate with cross-functional engineering teams to integrate predictive analytics into operational workflows.
- Conduct deep-dive statistical analyses to identify trends, seasonal patterns, and anomalies in complex data streams.
- Automate data pipelines and improve model performance using rigorous validation and backtesting frameworks.
- Communicate complex analytical insights to non-technical stakeholders to influence strategic business outcomes.
- Maintain high standards of model documentation and version control to ensure reproducibility and compliance.
- Continuously research and implement emerging machine learning techniques to stay at the forefront of the energy industry.
Kualifikasi
- PhD degree in Data Science, Computer Science, IT, Applied Mathematics, Statistics, Engineering, or a related quantitative discipline.
- Minimum GPA of 3.5 or equivalent academic excellence.
- Proven expertise in time series analysis (ARIMA, Prophet, LSTM, GRU, or similar deep learning architectures).
- Strong proficiency in programming languages such as Python or R, with experience in the scientific stack (NumPy, Pandas, Scikit-Learn, PyTorch/TensorFlow).
- Solid foundation in SQL and experience working with big data technologies (Spark, Hadoop, or cloud-based data warehouses).
- Exceptional problem-solving skills with an ability to translate abstract business requirements into mathematical models.
- Strong interpersonal skills and the ability to work effectively in a diverse, global, and collaborative team environment.