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
Benefits
Flexible benefits with comprehensive medical coverage for self
Training and development opportunities
Subsidised rates at Ascott serviced residences
Strong advocate of staff volunteerism
Wellness programmes
Closing Statement
At CapitaLand, we advocate fair employment practices, and recruit talents based on merit and fit with our Corporate values. We provide equal opportunity for all qualified persons and build an inclusive workplace regardless of race, gender, age, religious belief, or nationality.
Only shortlisted candidates will be notified.