Overview
trying to build a core team of a handful of “data scientist” for an Enterprise Risk Management team in the business side of a Financial Services Institution.The goal is for this team to work with Quants, engineering folks and business to ideate and isolate signals from unstructured data, alternate data, multi-structured data, etc to better refine risk and fraud predictors.
It’s an urgent need, and it would help if you already have someone suitable in your deep network.
Company:
Yoh, A Day & Zimmermann Company
Qualifications:
Self-starters, been-there-done-that, individual-contributors, consultative and deep technology acumen. Some of the other areas that would be key for this role are:
– Good knowledge/experience in the Risk modeling, especially commercial risk
– NLU / NLP
– Good hands-on skills on Python, with good knowledge of NLTK libraries
– R
– Anomaly detection
– Neural Nets, deep learning algos, tensor-flow(TF)
