Python Job: Data Scientist - Associate

Job added on

Company

Morgan Stanley

Location

Mumbai - India

Job type

Full-Time

Python Job Details

Data Scientist - Associate

Job Number:

3227908

POSTING DATE: Dec 2, 2022
PRIMARY LOCATION: Non-Japan Asia-India-Maharashtra-Mumbai (MSA)
EDUCATION LEVEL: Bachelor's Degree
JOB: Compliance
EMPLOYMENT TYPE: Full Time
JOB LEVEL: Associate

DESCRIPTION

Job Description

Division: Legal & Compliance (LCD)
Super - Department: LCD CoE
Department: LCD Data & Analytics
Sub-Department:
Region: Asia/ India
Job Level: Associate
Job Title: Data Scientist
Employment Type: Full Time
Location: Mumbai Nirlon Knowledge Park

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.

LCD comprises of Legal, Compliance, Global Financial Crimes and Regulatory Relations.

The Legal Department provides guidance, requirements and procedures for understanding and complying with the laws, regulations and Firm policies that apply to our businesses.

The Global Compliance Department identifies applicable Compliance Obligations and maintains a Firmwide Compliance Risk management program, including Compliance Risks that transcend business lines, legal entities and jurisdictions of operation.

Global Financial Crimes is responsible for the development and governance of the Firm's financial crime prevention efforts across all regions and business units. Global Financial Crimes is comprised of the Anti-Money Laundering (AML), Sanctions, Anti-boycott, Anti-Corruption (ACG) and Government and Political Activities Compliance (GPAC) programs.

The Global Regulatory Relations Group (GRRG) is responsible for strategic and centralized management of the supervisory activities of Morgan Stanley's regulators and related developments globally, with a focus on regulatory reviews and examinations and continuous monitoring activities. GRRG serves as the central point of contact for the regulatory staff responsible for supervisory activities at Morgan Stanley entities and for timely reporting to Firm management and other governance or management bodies, as appropriate, on those relationships and supervisory processes, including areas of significant regulatory focus or concern.

LCD Center of Excellence — Mumbai (LCD CoE) is a part of Morgan Stanley's Global In-house Center, which provides global support to LCD and is an integral part of Firm and LCD strategy.

QUALIFICATIONS

Team Background

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 statistical and other quantitative techniques to improve surveillance and compliance monitoring and testing activities
Statistical analysis of model thresholds, back testing and other sensitivity and productivity analyses, model documentation and facilitate model validations.
Working with members of the Financial Crimes, Compliance, Legal and IT departments to identify, assess and manage risk by evaluating large data sets using various statistical tools.
Supporting periodic risk assessments through the analysis of data elements related to potential indicators of customer, product or geographic risk and identification of new quantitative factors that can be incorporated into the risk assessment process
Assisting in the creation of key risk and performance indicators in support of the oversight, monitoring and testing program.

Requirements

Skills required (essential)

Candidates must have:
Bachelor's or Master's Degree from premier institutes in mathematics, statistics, physics, computational finance, computer science or other quantitative fields
2-5 years of experience in advanced statistical analysis techniques including multi-variable data analysis and predictive modeling techniques. Hands-on and theoretical knowledge of various predictive modelling algorithms like XGBoost, Random Forests, K-means, DBSCAN, etc
Extensive experience using Python for statistical analysis and modeling. Experience in PySpark is a plus
Strong problem solving and project management skills with the ability to work independently and multi-task to meet deadlines in a rapidly changing environment.
Excellent written and oral communication skills

Skills Desired
Strong SQL knowledge with experience in writing complex queries
Experience in leveraging AI and ML frameworks/tools like TensorFlow, Keras, H2O or DataRobot
Expertise with Time Series problems is a plus