Responsibilities
- Work with business analysts and internal stakeholders to identify business problems and opportunities, propose analytics solutions, as well as data and technology requirements, and formalise them into a project. Analytics solutions include, but are not limited to report automation, descriptive analytics, and advanced analytics
- Work with data engineers to plan, identify, and integrate data from multiple source systems to enterprise data platform for analytics purposes
- Perform data exploration, preprocess, and analyse the data (both structured and unstructured); develop and deploy machine learning/deep learning models
- Create dashboards to communicate and present key findings to stakeholders, and manage UAT
- Work with the team to run and prioritise projects according to objectives and business impact
Requirements
- Bachelor's degree or equivalent experience in the quantitative field (e.g. Statistics, Mathematics, Computer Science, Engineering, etc.)
- At least 1 year of relevant work experience
- Good understanding of machine learning (eg. Logistic Regressions, SVM, Decision Tree, Random Forest, lightGBM, XGBoost) and deep learning algorithms (eg. CNN, RNN)
- Deep understanding of deep learning algorithms, and experience with open-source libraries such as TensorFlow, Keras, Pytorch, Scikit-Learn etc.
- Fluency in a programming language (e.g. Python, R, SQL, etc.)
- Familiarity with Big Data frameworks and visualisation tools (e.g. Power BI, Hadoop, Spark, Tableau, etc.)
- Good collaboration and communication skills to work effectively across teams and partner with business stakeholders