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.
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Technology works as a strategic partner with Morgan Stanley business units and the world's leading technology companies to redefine how we do business in ever more global, complex, and dynamic financial markets. Morgan Stanley's sizeable investment in technology results in quantitative trading systems, cutting-edge modeling and simulation software, comprehensive risk and security systems, and robust client-relationship capabilities, plus the worldwide infrastructure that forms the backbone of these systems and tools. Our insights, our applications and infrastructure give a competitive edge to clients' businesses-and to our own.
The Data Lake is a critical program under Wealth Management that has already been initiated a few months back. The Data & Analytics manager will be central to the data ingestion and curation areas under the DIGITAL and the Analytics & Data program to ensure curated and standardized data delivery to all consumers in the Wealth Management area.
Absence of a manager to this crucial business area will delay most of the deployment plans causing major losses to the investments already made in this area.
-Priority Programs impacted
Data Lake supports initiatives like DIGITAL, Analytics & Data program, Fraud Analytics, Analysis Driven Growth, PTI, Banking, etc.
-If Employee, why not consultant
This is a major area with a very high level of accountability. The candidate will be responsible for managing multiple vendor and FTE teams and hence, a consultant will not be the right choice for this position. In addition, it is crucial to retain critical data related IP within the firm and an FTE will be the right choice for this position.
-Why can't role be filled by the existing team
Don't have FTE
-What's the increase in demand/Driver behind the incremental ask
The Data Lake itself is a brand new initiative to cater to the analytics areas under the Digital & Analytics program. This has necessitated entirely new teams to handle the additional work load brought about by this initiative.
1. Domain and Business Analytics
a. The candidate should have over 15 years of relevant experience working as a data architect and analyst in a large investment bank or financial institution, preferably in the Wealth Management domain.
b. Excellent domain knowledge and experience with wealth management data with special emphasis on the following:
i. financial analysis,
ii. market data
iii. exposure to specific areas like Assets, securities, revenues, fixed income, alternative investments, insurance and annuities, portfolio management and advisory.
iv. Master data development and management
c. Hands on knowledge with visual and non-visual analytics with emphasis on extrapolation, intrapolation for predictive analytics and what-if scenarios.
2. Database and SQL
a. Candidate should be highly experienced with SQL and working with warehouse specific database technologies like Teradata, Greenplum and DB2-UDB.
b. Knowledge of working with Big Data viz., Hadoop and HDFS, noSQL DBs like Hive and HBase and programming using PIG.
c. Excellent hands on SQL development skills with evidence of having worked with complex SQL development for data feed setups and visual representation. Knowledge of ANSI-SQL constructs is a must.
3. Data modeling and architecture
a. Excellent and hands on experience in leading data discovery, conceptualization and modeling assignments.
b. Experience on aligning modeling to strategic warehouse architecture.
c. Ability to work with tools like ER-Win and Power Designer is an added advantage.
d. Experience working with ETL and reporting teams and ability to guide development teams in both areas with design implementations.
e. Excellent data mapping skills.
4. Reporting and Analytics
a. In depth hands-on experience with BI tools like Business Objects, Qlikview, Tableau and analytics tools like SAS, Alpine, Cognos.
b. Ability to guide visual analytics development teams from a modeling perspective.
A little about us:
Since its founding in 1935, Morgan Stanley and its people have helped redefine the meaning of financial services.