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 toolsincluding Alteryx, Excel, SQL, Python, and Tableauto 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: 

• Bachelors 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.