Senior Data Scientist

**Be a Part of Something BIG**
- Translate business requirements into problem statements, design and implement solution with analytics and/or AI/ML technology.
- Explore and build advanced capabilities for strategic initiatives such as anomaly detection, predictive maintenance, planning optimization, customer experience improvement, etc
- Analyse and provide analytical insights with business intelligence tools in meeting business expectation and objective.
- Extensive experience as a data scientist and familiar with data engineering or machine learning engineering techniques. Ability to relay insights in layman's terms, such that these can be used to inform business decisions.
- Lead and manage a team of young data scientists, data analysts, and MA/interns.
- Spearhead collaborations with external partners and working with consultant of Singtel AI COE on the AI/ML adoption.
- Lead in assessing and integrating AI/ML strategies with IT or other systems for our Networks AI/ML initiatives.
- Architect and drive solutions the new capabilities add on to the AI/ML platform as to cater the needed for Autonomous Networks use cases that uses AI/ML solution.

**Make An Impact By**
- Develop and deploy analytical projects (with and without Machine Learning solutions) from the large data sets from Big Data Platform with advance analytics tools.
- Develop machine learning models for predictive and prescriptive analytics (regression analysis, time series, probabilistic models, supervised classification, unsupervised learning, etc)
- Lead and monitor the performance of Junior Data Scientists and providing them with practical guidance, solution validation and implementation.
- Develop and deploy insight visualisation dashboard, analytics reports and conduct presentation to update to senior management on the outcome of the analytics/ML projects
- Train, build, validate, test, deploy, maintain, improve and fine-tune the models and algorithms. Selecting and employing advanced statistical procedures to obtain actionable insights.
- Build, maintain and improve the data cube model derived from telco datasets.
- Continuously optimize and explore the new technology through R&D and trial/PoC.
- Drive ML CoE within Networks and explore new use case and business opportunity such as 5G Use Cases, Anomalies detection, Operational Use Cases are to be pilot delivery in progress.
- Take charge in delivering and managing the E2E of AI/ML pipeline with AutoML, MLOps or equivalent and relevant capabilities.
- Responsible to review internal or external proposal such as vendor’s solution design to ensure technology appropriateness and standards compliance related to analytic and, AI/ML solution.
- Collaborate with different stakeholders from business, technical, project management and operation to design and implement the solution. Capable in work with Waterfall or Agile project team.
- Adopt and implement the industry standards and best practise of analytics project methodologies such as CRISP-DM for data mining, or similar.
- Mentor and coach junior and mid-level data scientists to foster skills development and career progression within the team.
- Evaluate and select advanced tools, frameworks, and methodologies to improve model accuracy, scalability, and deployment efficiency.
- Proactively identify high-impact opportunities where AI/ML can deliver business value, and lead the design of innovative, data-driven solutions.
- Lead technical reviews and post-implementation assessments to measure project impact and identify continuous improvement areas.

**Skills for Success**:

- Bachelor or Master’s degree in Computer Science, Math, Data Analytics, Data Science/Artificial Intelligence or Machine Learning with at least 2 years of hands-on development experience
- Hands on experience in analytics project and AI/ML model developments and deployment.
- Experience in handling large volume of datasets.
- Competent in machine learning principles and techniques.
- Analytical methods: statistical modeling (e.g. linear regression, time series), supervised machine learning (e.g., random forests, neural networks), design of experiments, segmentation/ clustering, text mining, NLP.
- Proficiency in Python, PySpark and analytics skillsets.
- Experience in programming, shell script and UNIX commands.
- EDA in using Jupyter or Zeppelin Notebook.

**Are you ready to say hello to BIG Possibilities?