Job Description
Enterprise Data Services is a newly formulated centralized group that plays a pivotal role in building the next generation of tools and platforms to address the data needs for end users and applications through the creation, maintenance and use of an Enterprise level data platform. This platform is being built to not only support data but also provide capabilities of centralized calculation engines for data accuracy and data consistency. This position reports into the Director of Enterprise Data Services as part of the organization under the Chief Data Officer.
The Data Analyst will serve as a flexible generalist by providing data to support performance requests in response to RFPs and analytical insight based on the requests from Investment and Business Development teams. The individual will utilize data analysis tools such as Excel, SQL, R or Python to collate data from various sources, analyze the information and provide insights and analysis to the requesting teams. In conjunction with IT, the individual will verify any new data being added to the Central Data Repository to sign-off on data completeness and accuracy from a business domain perspective.
Principal Duties
Partner with investment and business development teams to understand data needs with the ability to translate these needs into a comprehensive data solution
Ability to collate, interpret and analyze data to provide insights & drive business decisions
Use statistical models and industry recognized investment data calculation methodologies to perform various data analytics in SQL and MS Excel
Leverage quantitative methods to identify data patterns and perform quantitative analysis on investment performance and assets under management data
Establish and follow data management principles to improve data quality, lineage and governance
Partner with IT to build, test and validate calculations to provide easy and consistent access to data both for applications as well as end users
Exercise relational database knowledge to construct and execute SQL queries to be used in data analysis activities
Use other tools such as R and Python to manipulate data to address the information needs across the organization
Build and maintain strong relationships across the firm to understand CA’s business goals and prepare for the organization’s evolving data needs
Contribute to additional projects where relevant domain or data analysis expertise is needed
Qualifications
Bachelor’s Degree, with preference to Data Analytics, Information Systems, or Mathematics
3-5 years of industry experience in data analysis or in the financial sector
Willingness to learn and embrace a ‘jack of all trades’ mentality to build expertise and data depth across the entire Enterprise Data Services product suite
Demonstrated skill in SQL usage as part of data analysis
Working knowledge of R or Python is desirable but not required
Working knowledge of relational database design concepts
Demonstrated track record of working autonomously in a highly productive environment, executing with comfort in gray areas, and executing across multiple competing deadlines with fast-paced delivery targets
Excellent organizational, written and verbal communication skills
Demonstrated progression towards CIPM, CFA, and/or CAIA certification is a big plus
Direct experience integrating data from multiple sources such as client, fund, and market data domains strongly preferred
EQUAL OPPORTUNITY EMPLOYMENT
The firm is committed to the concept and practice of equal employment opportunity, and will not discriminate against any employee or applicant on the basis of race, color, religion, age, sex, national origin, sexual orientation, gender identity, disability, or veteran status. It is expected that all employees will follow a similar policy toward their co-workers.
Our clients trust the experience, leadership, and integrity of our investment professionals. Working with some of the world’s most sophisticated institutional investors for more than 40 years, we bring a deep knowledge of portfolio management best...
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