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Data Scientist

Salary undisclosed

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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.