- Working cross-functionally with business managers/product managers/engineers and designers to gather requirements and to understand their business processes
- Applying machine learning techniques, in core subject areas including: filter life time predictions, air quality management, IIoT, logistics processes and industrial filtration.
- Designing experiments and back-test algorithms using historical data
- Making strategic data architecture recommendations
- Implementing data science experimental framework to enable organization-wide experiments
- Design, develop, test and deploy analysis, hypothesis, and machine learning models that solves business challenges and uncovers insights to enhance business performances
- Design, implement, and manage data analytics pipelines from end-to-end
- Collect, cleanse and transform data from multiple data sources for report generation and visualization for business units and technical audiences
- Develop machine learning classifiers, algorithms and processes
- Data mining of data sets of various types and formats
- Document all aspects of software design, development, debug and release
As a successful applicant, you would have a Masters Degree/PHD in Computer Science or a related technical field with the ability to manage stakeholders and communicate well. You will have strong experience in Machine Learning with at least 5 years of Python or R development experience and good experience in SQL, with the following desirable skills/experience:
- Proficient in programming languages such as Python or Java is required
- Extensive data analytic experience in Pandas, NumPy, scikit-learn, Jupyter, R, etc.
- Demonstrated experience applying and showing an understanding of machine learning algorithms for classification, regression, clustering, etc.
- Developed and deployed applications running on public cloud systems, such as AWS/Azure or equivalent
- Experience with common data science tools such as R, python, scipy, sagemaker, Big data technologies, Tableau and machine learning tools
- Experience working in Hadoop ecosystem and Spark is a plus
- Good applied statistics skills such as distributions, statistical testing, regression, etc
- Ability and desire to learn and pick up new tools and technologies for problem solving, enhancing analysis results and accuracy, and optimizing workflow efficiency
- Independent and possess creative problem solving skills to address business problems from different perspectives
- Ability to distil and communicate data to all organisational levels
- Practice a lean agile scrum process to continuously deliver value to customers
- Able to interact with development teams to determine project requirements