Knowledge/Experience:

• A bachelor’s degree in data science, data analytics, computer science, mathematics, statistics, econometrics, financial engineering, computer or electrical engineering, or other related quantitative fields. More advanced degree preferred.


• An understanding of Machine Learning and Artificial Intelligence (AI)


• Experience with common data science toolkit such as SQL, Python (including Pandas, SciPy, Scikit-learn), Hadoop, Spark, TensorFlow,


• An understanding of statistics (especially algebra and probability theory) and financial economics (especially quantitative risk analysis and asset valuation)


• Experience with data visualization tools (e.g., Tableau) and statistical packages (e.g., SAS)


• Experience with analysis in housing and mortgage markets as well as fixed income preferred.

Skills/Qualifications:

• Strong analytical skills and ability to work as part of a fast-paced team.


• Business acumen to understand complex business problems and translate them into analysis that leads to actionable business insights.


• Strong communication skills (oral and written) to explain complex data and analytical problems.


• Willingness to learn and to explore new ideas, with independent thinking and attention to details.


• Strong work ethics, the can-do attitude and excellent interpersonal skills.