Quant Analytics Associate Senior
Quant Analytics Associate Senior
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1 Vacancy
Job Description
If you are passionate about leveraging data to drive strategic decisions and optimize financial outcomes then you have found the right team
As a Quant Analytics Associate Senior in the Collections and Recovery operations you will collaborate closely with business partners and stakeholders to set quantifiable goals identify opportunities and implement strategies through experimentation influencing business direction and supporting data-driven decisions that directly impact the financial bottom line. You will optimize results using data governance strategy development testing reporting data science and machine learning disciplines to understand and predict customer behavior and industry trends enhancing recovery channel performance.
The Consumer and Community Banking Operations division at Chase provides a wide range of financial services including personal banking credit cards mortgages auto financing investment advice small business loans and payment processing. Within this division the Recovery Analytics and Business Execution team leverages data to create competitive advantages and generate critical analytical insights that support Collections Operations for Credit Card Overdraft Deposits Auto and Business Banking products.
Job Responsibilities:
- Demonstrate strong analytical skills to collect organize analyze and disseminate significant amounts of information with attention to detail and accuracy.
- Understand drivers underlying data and core business processes to support strategic direction with independent and thoughtful analytics managing channel performance addressing complex issues and generating forward-looking solutions.
- Collaborate across functions (data management risk strategy and other analytics resources) to implement best practices and explore new data sources to support critical strategies.
- Monitor internal and external customer/industry trends provide critical insights and deliver business narratives and presentations summarizing sharp insights and conclusions.
- Become a subject matter expert and trusted partner to our customers to formulate quantifiable goals generate timely insights communicate compelling business narratives and advise on strategies with experimentation to support ongoing process/product/channel improvement.
Required Qualifications Capabilities and Skills:
- Bachelors degree in Statistics Economics Econometrics Operations Research Mathematics Finance or equivalent quantitative field with 5 years of applied analytical experience in complex and large data environments or a Masters/MBA degree with 3 years of applied analytical experience.
- Intermediate to advanced knowledge in statistics finance analytics and predictive modeling.
- Proven experience with programming languages (SQL SAS R Python Alteryx) relational databases (Oracle/Teradata) and visualization tools (Tableau) to create/manage/analyze large data sets.
- Utilize a sense of urgency be proactive and result-driven with attention to detail. Build a solid understanding of the business actively seek input to anticipate needs and work to meet and exceed them.
- Be well-organized focused on results. Follow a logical and structured approach to support deliverables and manage multiple priorities set high standards for self; accountable to deliver commitments on time and with high quality with a focus on results and continuous improvements.
- Proven problem-solving skills and effective and clear communication with a variety of business partners.
Preferred Qualifications Capabilities and Skills:
- PhD degree in a quantitative field
- Deliver amidst continuous change in an agile and demanding work environment effectively optimizing delivery of business goals and return on investment.
- Monitor trends and develop key partnerships to advise on the use of new approaches and technologies.
- Positive culture carrier embrace a growth and learning mindset; curious and creative; collaborative team-oriented and client-focused; motivated by business and technical challenges
Schedule:
- Monday through Friday 8:00 am to 5:00 pm.
- This is a Hybrid position requiring the incumbent to commute/work on-site 3 days a week and work from home 2 days a week. Expected to become full in-office presence in Q1/Q2 2026
Note: This role does not offer visa sponsorship.
Required Experience:
IC
Employment Type
Full-Time
