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Quant Analytics Lead-Vice President

JPMorgan Chase

Quant Analytics Lead-Vice President

JPMorgan Chase

Columbus, OH, United States, US

·

On-site

·

Full-time

·

5d ago

Join the Alternative Lending Analytics Team and play a pivotal role in shaping the future of the Connected Commerce lending business.

As Quant Analytics Lead within the Alternative Analytics team, you will partner with cross-functional teams to analyze data from large SQL and AWS databases, translating insights into actionable recommendations for stakeholders. You’ll need strong analytical rigor and a deep sense of curiosity. You will play a key role in launching new lending products and driving their growth, collaborating with both analytic and non-analytic groups to shape strategy and influence business decisions. This position is ideal for an innovative leader who thrives in a dynamic environment and is passionate about using data to deliver measurable business outcomes. You will lead the delivery of analytics and insights to inform strategies and influence critical business decisions.

Job responsibilities

  • Establish and foster partnerships across the organization to understand business requirements.
  • Lead the creation and execution of solutions to pull and combine data from multiple sources for lending product reporting.
  • Develop analytics frameworks for new lending products.
  • Collaborate with data partners to ensure data quality and integrity for new lending products.
  • Lead report automation initiatives.
  • Analyze customer, transaction, and product usage data to identify actionable insights.
  • Communicate insights to senior leaders to influence strategy and business decisions.
  • Translate complex analyses into concise executive narratives and visuals to support strategic decision-making.
  • Manage multiple priorities and deliver results quickly with rigor.

Required qualifications, capabilities, and skills

  • BS in an applicable STEM field and 6+ years of financial industry experience in business analytics roles (e.g., marketing analytics, risk analytics, product analytics, business insights).
  • 6+ years of hands-on experience working with a broad range of analytics technologies and tools (SAS, SQL, Spark, Python, Unix, Excel Pivot, etc.) in a big data environment.
  • Financial services experience, especially in credit card or mortgage analytics.
  • Exceptional communication skills, with the ability to convey complex information in an understandable, compelling, and persuasive manner to both technical and non-technical stakeholders.
  • Ability to identify key drivers, prioritize tasks, be results-oriented, and demonstrate strong attention to detail.
  • Proficient in applying quantitative methods for business analytics.
  • Adept critical thinker and problem solver.

Preferred qualifications, capabilities, and skills

  • Master’s degree in a relevant quantitative field (e.g., Statistics, Economics, Marketing Analytics, Mathematics, Engineering, Computer Science, or related fields)

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About JPMorgan Chase

JPMorgan Chase

JPMorgan Chase is a multinational investment bank and financial services company that provides banking, investment, and asset management services globally. It is one of the largest banks in the United States by assets and market capitalization.

300,000+

Employees

New York City

Headquarters

Reviews

4.2

10 reviews

Work Life Balance

4.2

Compensation

4.3

Culture

4.5

Career

4.4

Management

4.1

75%

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Pros

Good pay and benefits

Work-life balance

Career advancement opportunities

Cons

Heavy workload at times

Career advancement takes time

Pay could be better in some roles

Salary Ranges

47 data points

Junior/L3

Mid/L4

Senior/L5

Junior/L3 · Analyst

21 reports

$126,500

total / year

Base

$110,000

Stock

-

Bonus

-

$95,450

$155,250

Interview Experience

4 interviews

Difficulty

2.8

/ 5

Duration

14-28 weeks

Interview Process

1

Application Review

2

HireVue Video Interview

3

Technical/Behavioral Assessment

4

Final Interview Round

5

Offer Decision

Common Questions

Behavioral/STAR

Technical Knowledge

Past Experience

Culture Fit

Case Study