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 platforms 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.
Requirement
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.