Quant Modelling Lead - Vice President, Financial Analysis

JPMorgan Chase JPMorgan Chase · Banking · New York, NY +1 · Corporate Sector

Lead a team of analysts and data scientists to enhance analytical capabilities by integrating traditional financial modeling with data science techniques, focusing on financial models, forecasting, and predictive modeling within a fintech environment.

What you'd actually do

  1. Oversee the design, development, and implementation of financial models and forecasting tools that derive actionable insights for senior leadership in Financial Analysis.
  2. Analyze large datasets to extract meaningful insights and trends.
  3. Innovate and design predictive models and sophisticated data science methodologies that blend traditional corporate finance with modern analytical techniques.
  4. Conduct exploratory analyses to identify patterns and opportunities for improvement.
  5. Work closely with stakeholders across Finance, Risk and technology to understand business needs and translate them into analytical solutions.

Skills

Required

  • Advanced degree in Finance, Quantitative Finance, Data Science, Economics, or a related field.
  • A minimum of 5 years’ experience in financial modeling, forecasting or quantitative research within a leading financial organization.
  • Deep expertise in data science, statistical analysis and model development is required
  • Strong programming/scripting skills (incl. Python, R).
  • Proficiency in traditional financial tools (advanced Excel, financial software) and advanced PowerPoint skills.
  • Strong analytical, problem-solving skills and attention to detail.
  • Exceptional communication skills with a proven ability to prepare and deliver executive-level presentations.
  • Ability to work independently and as part of a team. Experience managing and mentoring cross-functional teams, cultivating a collaborative environment.
  • A results-driven mindset paired with a relentless intellectual curiosity, quick thinking, and the ability to innovate solutions that bridge data science and corporate finance.

What the JD emphasized

  • strong analytical and corporate finance background
  • deep finance expertise and industry knowledge
  • strong analytical skillset
  • strong foundation in data science techniques—including Artificial Intelligence, Machine Learning, and advanced econometric methods is essential
  • experience in finance related modeling concepts is highly valued
  • Deep expertise in data science, statistical analysis and model development is required