Department: WM ANALYTICS & Data Technology
Job Location: Bangalore
Morgan Stanley is a leading global financial services firm providing a wide range of investment banking, securities, investment management and wealth management services. We advise, originate, trade, manage and distribute capital for governments, institutions and individuals. 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.
Wealth Management and Investment Management Technology (WMIMT) is responsible for the design, development, delivery, and support of the technical platform behind the products and services used by the Business.
Morgan Stanley Wealth Management (WM) is a product of the acquisition of Smith Barney from Citigroup, which was completed in June ?13. Its core client base is individual investors, small- to medium-size businesses and institutions, and high net worth families and individuals. In the second half of ?14, WM reached a milestone, with its business having surpassed $2 trillion in total client assets. Morgan Stanley has recently acquired Solium and E-trade to further bolster its Wealth Management business.
Candidate will work with the Machine Learning & Advanced Analytics team, based out of Bangalore, working on various deliveries. This candidate will be reporting to the Local Analytics lead in Bangalore and work in collaboration with rest of the team in India & NY. Candidate will be working hands-on on analytical projects with big data development and be responsible for project delivery, execution and support. Candidate should be able to work in a dynamic environment with limited or no supervision and should be able to motivate junior team members. Should be comfortable and manage time working with global team on multiple initiatives. Candidate will be able to extract, explore, mine and experiment with data to answer critical business problems. While uncovering insights and identifying patterns are necessary, candidate is expected to have strong programming skills in Hadoop, Hive, Spark ML, SparkSQL and cloud experience Azure, AWS, GC techniques.
The Right Candidate – ML Engineer
4-6 years of working across Analytics & Banking domain.
Strong programming experience in Python/Scala
Extensive experience in Data Analysis - Skilled in uncovering insights and identifying patterns
Proven experience in Data Analysis Python
Good understanding of Statistics.
Must have strong SQL experience
Expertise in handling large data volumes in distributed systems
Strong command over Big Data technologies – Hadoop, Hive, Impala, Spark
Good experience in Linux-based Environment
Ability to work in fast paced and dynamic environment.
Excellent Communication and presentation skills
Experience working with global teams.
Good to have skills
Understanding of various event-based queue platforms (Kafka, Azure Service Bus, Event hub)
Experience with Java or Scala will be a big plus.
Experience of developing Data Pipeline for ML Applications
Exposure to microservice based architecture.