Data Analyst - Vice President

  • Competitive
  • New York, NY, USA
  • Permanent, Full time
  • Morgan Stanley USA
  • 18 Nov 17 2017-11-18

Data Analyst - Vice President

organ Stanley's business around the world is supported by groups and teams with a wide variety of specialized skills. They provide information and strategic thinking to the Management Committee; help to ensure the long-term growth and efficient day-to-day functioning of our business; and serve the well-being of our shareholders, clients and employees.

The Fixed Income Division is comprised of Interest Rate and Currency Products, Credit Products and Distribution. Professionals in the Division assess and actively manages risk, trade securities, and structure as well as execute innovative transactions in the fast-paced and constantly changing global markets. The Commodities Division is a market leader in energy, metals, and agricultural product trading worldwide whose professionals trade in both physical and derivative commodity risk.

We are looking for a self-motivated, innovative, hard-working individual who can handle changing priorities and multiple tasks in a timely fashion.

As a quant developer and modeler, you will build tools to query, clean, and analyze raw data by filtering through large databases and develop models for pricing, hedging, and risk management for securitized and corporate credit products.


Your duties will include implementing and maintaining Q- and shell-based scripts used to update databases and run models; managing large kdb+ databases; and designing, fitting, implementing, and debugging sophisticated econometric models in a team-oriented environment with significant growth opportunity.

• Advanced degree in Computer Science, Engineering, Mathematics, Statistics, or related quantitative field or equivalent
• Strong programming skills; experience with programming languages including Q/KDB, C/C++, Java, Python, R; working in a Linux environment using Unix command-line tools
• Strong quantitative and problem solving skills; proficiency working with large datasets, statistical methods, machine learning, numerical methods, algorithm design and implementation
• Strong verbal and written communication skills; ability to act as a bridge between several business areas
• Diligent and meticulous individual with the ability to "think outside the box"