Research Officer (Advanced Intelligence Lab)
Position Purpose & Summary:
The research officer will be responsible to conduct a range of research which supports data analytics in its mission. In particular, this role may involve working across a variety of research activities in statistics/mathematics or business analytics with experience, courses, or project work in analytic methods such as regression, classification, deep learning, modelling, time series analysis, pattern recognition, queuing theory, multivariate analysis, and other various predictive analytics techniques. He/she is involved in all areas of R&D from design, implementation, and optimisation. This leads to creating insight and innovations which unlock the power of data science.
Primary Duties & Responsibilities:
- To perform data pre-processing in extract, transform and load (ETL) with various data sources
- To select features, building and optimising classifiers using machine learning techniques
- To execute data mining, machine learning and deep learning by using state-of-the-art methods
- To evaluate and fine-tune hyperparameters and their predictive models
- To enhance data collection procedures to include information that is relevant for building analytic systems
- To draw conclusions from data and prescribe actionable, measurable activities and data visualisation
- To work on research publications and applications for patents
Accountability:
- Completing any tasks that have been designated to him/her
- Being responsible for assigned duties that go along with his/her tasks
- Being consistent in doing the right thing in all aspects pertaining to his/her tasks
- Working together towards a common goal for the organisation
Academic Qualification:
- Degree
- Engineering
- Information Technology
Technical Skills
- Good understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc.
- Experience in extracting and processing various data source formats such as CSV, JSON, HDF and database Experience in data science toolkits, such as Jupyter Notebook, Pandas, NumPy, TensorFlow, PyTorch, H2O.ai, rapids. ai, etc.
- Strong in at least two of these are highly desirable. Innate ability in applied statistics skills, such as distributions, statistical testing, regression and others.
- Good in using Python, SQL, C/C++, Bash, JavaScript, HTML 5 and CSS
Academic Qualification:
- Degree
- Engineering
- Information Technology
