Work with Line of Business (LOB) data owners to identify, understand, and deliver critical metrics to measure operational service performance and Client Experience (CX).
Perform project analysis, including documenting business requirements, detailing issues and risks, and drafting business processes and data flows
Perform data analysis, including data collection, synthesis, and translation of results into concrete metrics or deliverables
Define data taxonomy and requirements for functional partners. Work with minimal direction/independently, keeping management informed of progress and escalating issues
Assist in ad-hoc data-mining, data-representation and analysis as may be required by the business
Understand current data architectures and leverage for measurement of success and identification of opportunities.
Develop data driven insights into Client Service, including historical comparison, global variability, future trends and understanding of key drivers.
Rapid prototypes to iteratively drive transformation agenda and validate impact to end-users.
Own the strategic partnerships with expert analytics and technical teams to enhance our data and data analysis offering
Work closely with data science, AI/ML and business teams to drive the end-to-end lifecycle of our products
Partner with technology teams to ensure a successful deployment of analytics products
Required Qualifications, Skills and Capabilities
Degree in a quantitative discipline, e.g., Engineering, Sciences, or similar in competitive BSc degrees.
7+ years of experience in financial services organization (Sell-side firm is a plus)
Data analytics skills covering as a basis, but not limited to MS Excel, access database, Alteryx, Tableau for business and data analysis.
Intermediate to Advanced SQL skills.
Data literacy and comfort to engage with AI, Machine Learning partners for analysis tasks – python and R skills for data analysis is a plus.
Able to work with non-specialists in a partnership model, conveys information clearly and creates a sense of trust with stakeholders.
Practical experience with data analysis and comfort with rapid prototyping and experimental design.
Ability to influence multiple stakeholders without direct authority.