Data Scientist, Legal and Compliance Division

Data Scientist, Legal and Compliance Division

Company Profile
Morgan Stanley is a leading global financial services firm providing a wide range of investment banking, securities, investment management and wealth management services. The Firm's employees serve clients worldwide including corporations, governments and individuals from more than 1,200 offices in 43 countries.

As a market leader, the talent and passion of our people is critical to our success. Together, we share a common set of values rooted in integrity, excellence and strong team ethic. Morgan Stanley can provide a superior foundation for building a professional career - a place for people to learn, to achieve and grow. A philosophy that balances personal lifestyles, perspectives and needs is an important part of our culture.

Department Profile
Professionals within the Legal and Compliance Division (LCD) provide a wide range of services to our business units. They might help to structure a complex and sensitive cross-border transaction; advise on a new product introduction; develop a training program or defuse an investor dispute. They preserve the firm's invaluable reputation for integrity and protect the firm from sanctions with policies and procedures that meet regulatory requirements around the world. They also strive to maintain cooperative relationships with governmental policy makers and the regulatory and self-regulatory agencies that govern the firm's businesses.
Data & Analytics is a function in the Legal and Compliance Division responsible for designing and optimizing surveillance models, approaches and tools using advanced analytical techniques like supervised and unsupervised machine learning, Natural Language Processing (NLP) and evolving techniques like reinforcement and deep learning as well as graph analytics. The surveillances and other tools help identify suspicious and/or illegal behaviors like money laundering, market manipulation, insider trading, unfair sales or trading practices and other financial crimes.

Primary Responsibilities

- Development of Risk models leveraging Machine learning and related quantitative techniques to improve surveillance and compliance monitoring activities
- Develop and implement new risk identification strategies including graph-based approaches, graph analytics infrastructure and data sourcing efforts
- Undertake research efforts to identify novel methods to deliver efficiency and effectiveness across analytical solutions
- Work with stakeholders of the Financial Crimes, Compliance, Legal and IT departments to champion the adoption of new AI and ML approaches, techniques and capabilities

Qualifications:

Required Skills

- Master's Degree in Computer Science, Machine Learning, Statistics, Mathematics, Engineering or other highly quantitative field. PhD preferred
- 4-7 years hands-on industry experience in building supervised and unsupervised machine learning based solutions and applied statistical analysis to solve complex business problems
- Knowledge of software design principles and excellent skills in one or more programming languages including Python, R, Java, Scala
- Ability to work with and mentor a global team balancing multiple projects
- Strong problem solving and project management skills
- Excellent written and oral communication skills

Preferred Skills

- Familiarity with Financial Markets, with an emphasis on Financial Crimes, Compliance or Fraud analytics.
-Experience with graph and network analytics packages such as NetworkX or Neo4J
- Experience with deep learning frameworks including PyTorch or Tensorflow
- Experience with big data tools such as Hadoop & cloud computing, such as PySpark and cloud machine learning tools.
Expected base pay rates for the role will be between 85000 and 135000 per year at the commencement of employment. However, base pay if hired will be determined on an individualized basis and is only part of the total compensation package, which, depending on the position, may also include commission earnings, incentive compensation, discretionary bonuses, other short and long-term incentive packages, and other Morgan Stanley sponsored benefit programs.