The Role
The Data Scientist will implement cohesive data integration and analytics solutions involving both structured and unstructured data. Projects will include development of predictive, forecasting or operation research (optimisation) models as well as text mining and network analytics solutions.
Job Responsibilities
· Primarily responsible for applying the skills and knowledge gained about data analysis, analytics, data science to ensure the successful delivery of client engagements and initiatives within our Data and Analytics practice.
· Develop and manage the end-to-end lifecycle of analytics projects from requirement, data scoping, modelling to production (model deployment and monitoring).
· Attend and assist in facilitating project meetings / workshops with client working team members.
· Propose, implement, and validate algorithms, ensuring functional and non-functional requirements such as transparency, fairness, scalability, security, integration complexity and operational costs.
· Participate in software development processes and best practices, documentation of requirements and software codes during the software development lifecycle.
· Produce high quality deliverables/document, with-ready-to-use content.
· Drive a module or task within a project on their own with minimal supervision.
· Prepare user requirements and any data development work including documentation.
· Proactively perform research on the business, industry and functional domain of the client to stay up to date.
· Assist in developing project deliverables and assets such as templates, processes, reports, and presentation decks for the client based on the work assigned.
Job Requirements
· Bachelor’s degree in computer science, Mathematics, Statistics, Business Analytics or equivalent.
· Data Scientist – at least 2 years’ experience in data analytics fields/ML.
· Experience in data processing, feature selection, hyper-parameter optimization, model validation and visualization.
· Experience in data analysis / numerical computing / classical ML tools like Pandas, NumPy/SciPy, Scikit-Learn, or XGBoost.
· Able to develop SQL queries and working with data models.
· Experience in production software engineering routines such as test-driven development, code versioning with Git, conducting code reviews, and CI/CD.
· Familiar with object-oriented programming concepts and their application to data science pipelines.
· Deep and eager interest in emerging technologies and the ability to leverage the technologies into solutions to meet our strategic and operational client needs.
· A self-starter with an analytical approach to problem solving.
· A client-centric, outcome driven and quality focused team player.
· Detailed oriented and is able to work in fast paced and agile environment.
· Excellent communication skills; both in written and spoken English.
Office Location : Central
Hybrid working arrangement
**We regret that only shortlisted candidates will be notified. Personal data collected will be used for recruitment purposes**
