Internal Audit Data Scientist

  • Competitive
  • New York, NY, USA New York NY US
  • Permanent, Full time
  • Morgan Stanley USA
  • 17 Mar 18 2018-03-17

Internal Audit Data Scientist

Morgan Stanley is seeking a strong Data Scientist in its internal audit department to help integrate advanced analytics techniques in audit planning, fieldwork, and risk assessments. The candidate will be working on innovative and strategic projects to help identify emerging risks and also help with audit scoping. This is a great opportunity to partner with strong data analytics leads in order to use machine learning in providing new ways to evaluate and assess the control environment.

The data scientist will manage multiple audit and project assignments and collaborate closely with data analysts, audit colleagues, and other analytics teams at Morgan Stanley. Candidate must have strong communications skills and be able to explain the results to a non-technical audience. In addition, the candidate should demonstrate the ability to manipulate data from multiple and be comfortable working on unstructured assignments where the scope is not always defined upfront.


Candidate should have strong skills in R or Python and a good understanding of statistics and new machine learning techniques.

Three to seven years of experience in a data scientist or analytics role with hands-on experience working with model development.

Experience working with unstructured text analytics including NLG, NLP.

SQL and knowledge of data extraction and manipulation techniques including the ability to stage and import large volumes of data.

Strong communication skills and ability to thrive in a fast paced, multiple deliverables, team-oriented environment

Working knowledge of tools for data analysis, including business intelligence products such as Qlikview, Tableau, etc. Understanding of basic UNIX commands and the ability to manipulate files and logs using shell or Perl scripts*LI-ND1