Job Description & Requirements

Be a Part of Something BIG!

Translating business requirements into problem statements, design and implement solutions with analytics, machine learning, or state of the art AI technologies.

Explore and build advanced capabilities for strategic initiatives such as anomaly detection, predictive maintenance, planning optimization, customer experience improvement, etc

Analyse, uncover, and provide analytical insights with business intelligence tools in meeting business expectations and objective.
Extensive experience as a data scientist and familiar with data engineering and machine learning engineering techniques. Ability to relay insights in layman's terms, which can be then used to inform business decisions.
Lead and mentor a team of junior data scientists and promote capability growth within the team.
Spearhead collaborations with external partners and working within the AIDA cross functional squad to deliver strong business impact.
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

Discover, Develop and deploy analytical projects (with or without AI & Machine Learning components) from the sizeable network data sets from Big Data Platform with Advanced 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 dashboards, analytics reports, Generative AI based information aggregations and conduct presentation to update to senior management on the outcome of the analytics/ML projects
Train, build, validate, test, 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 use cases within Networks domain and explore new use case and business opportunities such as 5G Use Cases, Anomalies detection.
Responsible to review internal or external proposal such as vendor's solution design to ensure technology appropriateness, solution efficacy 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 practice 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.
Lead cross-functional analytics initiatives and drive alignment across business units to ensure the strategic application of data science.
Evaluate and select advanced tools, frameworks, and methodologies to improve model accuracy, scalability, and deployment efficiency.
Serve as a subject matter expert (SME) in AI/ML within the organization and represent the team in technical forums, external collaborations, and industry events.
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 5 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.
Good interpersonal skills
Highly self-driven, demonstrate critical thinking, team player & fast learner
Outstanding supervision and mentorship abilities.
Good technical writing skills

Lead Data Scientist