WHAT YOU’LL DO
• Data Analysis & Model Development
o Research and develop statistical and machine learning models for comprehensive data analysis
o Utilize algorithms and models to mine big data, perform data and error analysis, and ensure data uniformity and accuracy
o Apply data mining techniques and perform statistical analysis to generate insights at scale
• Collaboration & Solution Development
o Work closely with both internal and external stakeholders to understand analytic needs and develop effective solutions
o Create machine learning-based tools or processes, such as recommendation engines, and monitor their performance through A/B testing and predictive capabilities
o Communicate analytic solutions to stakeholders and implement necessary improvements to operational systems
• Innovation & Capability Building
o Identify relevant structured and unstructured data sources for mining meaningful insights
o Build prototype analysis pipelines iteratively to provide scalable insights
o Contribute to building data analytics capabilities across the organization, emphasizing the strategic value of data in achieving business objectives
Job Requirements
• Tertiary qualification in a quantitative discipline such as Computer Science, Economics, Statistics, or Applied Mathematics.
• 3-8 years of experience in computer science, applied mathematics, or other quantitative/computational disciplines.
• Proven experience in data visualization tools (e.g., Tableau) and data analysis/processing tools (e.g., R, Python).
• Experience with Cloud Technology (e.g., AWS data and analytics Tech Stack) and distributed computing tools (e.g., Hadoop/Spark).
• Demonstrated ability in building machine learning models at scale, using real-time data pipelines on platforms.
• Strong analytical skills with the ability to communicate complex quantitative analysis in a clear, precise, and actionable manner.
• Proficiency in data engineering, including SQL and manipulating structured and unstructured data sources for analysis.
• Advanced skills in pattern recognition and predictive modeling.
• Experience or specialization in fraud prevention/detection, compliance, forensics, or Jobs and Skills related analysis will be considered advantageous.
• Excellent communication and presentation skills, with a strong emphasis on collaboration and innovation.
