Job Description

The job description is comprehensive and well-structured, but it could benefit from clearer segmentation and some minor formatting improvements for enhanced readability. Here's a refined version:

Qualifications

• Master's Degree in Mathematics, Statistics, Economics, or other quantitative disciplines
• 8-10 years of research, data science, or analytical modeling experience in relevant domains
• Familiarity with:
• Statistical and technical analysis tools (R, Python, SQL, SAS, Cognos, etc.)
• Automated machine learning tools (Matplotlib, RapidMiner, DataRobot)
• Retail banking or transaction processing industries

Technical Skills

• Strong quantitative background for statistical analyses and coding
• Fluency in risk analytics, pricing, risk modeling
• Experience with pattern recognition or machine learning
• Data mining, manipulation, analysis, visualization, and reporting tools
• Handling large datasets; experience with distributed computing tools (Map/Reduce, Hadoop, Hive) is a plus

Research and Analytical Mindset

• Ability to structure projects from idea to implementation
• Manipulate and analyze complex, high-volume, high-dimensional data from diverse sources
• Passion for empirical research and data-driven problem solving
• Flexible analytical approach for varying levels of result precision
• Effective communication of complex analyses to non-technical stakeholders

Personal Attributes

• Driven, focused self-starter with excellent communication and follow-through skills

What Your DNA Looks Like

• Passion to win: Thrive in competitive environments and aim to be a market leader
• Communicative: Strong interpersonal skills and ability to present information effectively
• Resourceful: Independent worker with a problem-solving mentality
• Organized: Ability to prioritize tasks and work with a sense of urgency

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