Lead' Data Scientist

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