Data Scientist II
Worley
- Kuala Lumpur
- Permanent
- Full-time
- We deliver the world’s most complex projects
- Join a high-performing team
- Our mission is to make energy affordable and accessible to everyone - enabled by providing our clients with 5 key capabilities: Digital Advisory services & Human-Centric Service Design.
- End-to-End Digital Twins as a foundation for smart advisory
- Take advisory services & breakthrough analytics solutions to the next level by productizing them and serving them to our clients & ecosystem through user-centric B2B marketplace.
- Sustainability solutions.
- Autonomous solutions design and implementation.
We complement conventional engineering approaches to solving problems, by leveraging subject matter expertise and domain knowledge alongside simulation-driven design, data science and machine learning.
Our solutions increase operational safety and protect against losses, while optimised asset designs, operational parameters and maintenance strategies deliver significant savings.Responsibilities will include:
- Collecting and cleaning data from various sources: working with large and complex datasets and using programming languages such as Python or R to clean and process the data, ready for analysis.
- Analysing and interpreting data: Using statistical techniques and machine learning algorithms to identify trends, patterns, and insights in the data.
- Building predictive models: Creating mathematical models that use historical data to forecast future trends and behaviours.
- Communicating findings: Presenting findings and recommendations to stakeholders in a clear, compelling, and actionable manner.
- Continuously monitoring and updating models: Continuously monitoring the performance of models, updating them as necessary, and finding new ways to improve their accuracy.
- Collaborating with other teams in Customer Solutions and Worley: Working with other teams within the organisation, such as sales and marketing, Solutions Factory (DevOps and data systems), PMO, and project teams. Understand customers’ challenges, agree proposals, and deploy solutions.
- Staying current on industry developments: Continuously learning and staying informed of new technologies and trends in the field of data science to ensure that UIS is utilising the most effective techniques and tools.
- R&D/Product Development: Developing new commercial data science offerings, addressing industry needs, that Worley can take to market.
- Best practice: Establish governance, processes, systems, and code libraries that ensure consistent high standards of quality across the team.
- Management: coaching and line-management responsibilities subject to experience and team structure.
- Machine Learning
- Can demonstrate hands-on experience in at least four of the following machine learning applications: Regression, Classification, Clustering, Dimensionality Reduction, Deep Learning (AI), Reinforcement Learning, Optimisation.
- Au fair with current machine learning tools and platforms such as Python, IBM, Knime, Github, R, Spark, Weka, Amazon ML, Azure ML etc. * Analytical Knowledge- Design an analytical project incorporating the right approaches and datasets to solve a given problem.
- Mine data to understand its quality and distribution, informing model choice and transformations needed.
- Perform statistical tests on model output to assess performance and ensure the validity of conclusions. * Applied Analysis and Insight- Draw on domain expertise to choose the most appropriate analytical approach.
- Work with customers and subject matter experts throughout a project to ensure data is interpreted correctly and solutions are viable.
- Present models to non-technical audiences in compelling business-oriented terms.
- Present data in a visually compelling and elegant way making it easy to interpret and draw conclusions.
- Experience in analysis of IOT/Sensor Data to solve problems in an industrial setting. * Technical- Write code to access and process diverse data types from a range of on-prem and cloud sources.
- Familiar with cloud computing and big data technologies (Azure, AWS, Hadoop, Spark, Snowflake etc).
- Comfortable working on data platforms, such as Snowflake or Databricks, to manipulate data to engineer model features.
- Familiarity with the technologies used to validate, monitor and deploy ML models (Tensorflow, ML Flow, AWS Studio, Docker, Kubernetes etc). * Softer Skills-Spend time with customers to fully understand the challenges and the nuances of their organisation and data.
-Develop generalised approaches to solving problems in models and code.
-Bring data and analytics to life through storytelling, and excellent written and verbal skills.
-Be comfortable working in Agile project-management frameworks.QualificationsAbout You
- Undergraduate/Masters degree in STEM or other numerate subjects. Plus 3 or more years relevant working experience. OR
- PhD in a relevant field (Machine Learning, Industrial Analytics etc) plus one year commercial experience
- Join a fun and inclusive, global team of professionals.
- Opportunities to progress beyond this role.