Data Scientist - HSBC (NYC)

Top candidates will have a STEM Background; Business & Data Domain Knowledge (understanding of banking/financial services, data wrangling, exploratory and multivariate data analysis, data modeling, feature engineering, supervised and unsupervised machine learning algorithms); Programming / Engineering (e.g. Scala, R, Python, PuTTY for Linux) / (e.g. Apache Hadoop, Apache Spark); and Google Big Query stack is a nice to have (i.e. Tensorflow); and Tools / Frameworks (e.g., Anaconda, H20.ai, Spark MLlib, pandas, NumPy, Scikit-learn, ElasticSearch).  HSBC is looking for someone with a deep passion for solving hard problems and a willingness to do whatever it takes to advance their projects.  This is a position with great potential to have a wide impact.  

Anyone interested in applying should send their resume and cover letter with the email subject: "QMSS - HSBC Data Scientist" to all of the following people: Matthew Sattler at matthew.j.sattler@us.hsbc.com; Christopher Jen at christopher.l.jen@us.hsbc.com; and Greg Eirich at gme2101@columbia.edu.