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Data and Analytics - Quant Analytics Senior Associate
senior · Data Science & Analytics
Join a team that seeks for talented and highly motivated individual with exceptional data analysis skills.
As a Quant Analytics Senior Associate, within the Data and Analytics team, you will lead the analytics book of work and collaborate with a cross-functional team to support the Product and work closely with partners across Finance, Customer Experience, Design, Software Engineering, and Product Ownership.
Job Responsibilities:
Build holistic insights by integrating customer, account, digital, financial, and operational data sets to inform strategic decision-making.
Import, clean, transform, and validate data from multiple sources to prepare for advanced analytics and modeling.
Scope, implement, and track new features and enhancements within the collections journey to optimize customer experience and operational efficiency.
Identify customer interactions and events across various channels to gain a deeper understanding of customer journeys and pinpoint friction points.
Utilize a range of analytical and statistical tools—including Alteryx, Excel, SQL, Python, and Tableau—to analyze and interpret trends and patterns in complex data sets.
Support the creation and delivery of presentations that summarize key insights and actionable conclusions, often tailored for executive audiences.
Collaborate with business stakeholders to translate strategic objectives into actionable analytics initiatives and measurement frameworks and lead cross-functional projects, coordinating with product, technology, and business teams to deliver impactful analytics solutions.
Required Qualifications, Capabilities, and Skills:
Bachelor’s degree required, with a strong academic background and at least 4 years of experience building analytical solutions that integrate multiple data inputs from diverse sources, particularly in Marketing, Customer Journey, Operations, or Finance; Minimum of 2 years of hands-on experience in data analysis.
Demonstrated technical expertise in data modeling, data analysis, and segmentation techniques.
Proficient in Business Intelligence and analytical tools such as Alteryx and Tableau.
Self-sufficient in querying and extracting data from enterprise databases and data lakes, including platforms such as Snowflake, GOS, and AWS Athena.
Analytical rigor, with the ability to synthesize information across multiple platforms, systems, and organizations, and deliver superior data analysis.
Champion the use of advanced analytics techniques, such as machine learning and predictive modeling, to uncover deeper insights and drive innovation.
Establish and monitor key performance indicators (KPIs) to measure the effectiveness of analytics initiatives and inform ongoing strategy.
Preferred Qualifications, Capabilities, and Skills:
Experience developing financial business cases is highly desirable.
Operational knowledge of Document Services Operations is a strong advantage.
Background in analytics or experience within consumer or retail banking is preferred.
Familiarity with AWS technologies is a plus.