Data Scientist II

About the job

We’re looking for a Data Scientist II to join our Malaysia team. 

When you work for us, you get the chance to join nearly 50,000 people all driven by a common purpose of delivering a more sustainable world. We’re excited about the challenges ahead. We believe there’s never been a more rewarding time to work in the energy, chemical and resources sectors.

We offer a flexible approach to working, because our people are safer, healthier, and more productive when they can balance work with life. That’s why there are flexible and hybrid working options, so you can choose when, where and how you work.

As a Data Scientist II, you will be responsible for Analyse and interpret complex data to identify trends, patterns, and insights that inform business decisions. Utilise a wide variety of machine learning techniques, programming, and domain knowledge to develop predictive and prescriptive solutions to business problems.

Who we are

Worley is a global professional services company of energy, chemicals and resources experts headquartered in Australia.

Right now, we’re bridging two worlds as we accelerate to more sustainable energy sources, while helping our customers provide the energy, chemicals and resources that society needs now.

We partner with our customers to deliver projects and create value over the life of their portfolio of assets. We solve complex problems by finding integrated data-centric solutions from the first stages of consulting and engineering to installation and commissioning, to the last stages of decommissioning and remediation.Join us and help drive innovation and sustainability in our projects.

What you’ll do

We are looking for a Data Scientist II to join our team in Malaysia. 

The role responsibilities 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
  - Skilled at building predictive models to solve a wide range of problem types, choosing the right approach(es) to maximise performance. Seeks constantly to broaden repertoire of ML approaches used. Able to work in a variety of machine learning applications and coding libraries.
  - 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.