Data Scientist Associate-Wealth Management Advisor & Servicing Products

JobID: 210638637

Category: Predictive Science

JobSchedule: Full time

Posted Date: 2025-06-19T14:31:56+00:00

JobShift:

Base Pay/Salary: New York,NY $104,500.00-$140,000.00

Would you like to be part of a team that impacts the way wealth managers engage people in person? JPMorgan Chase needs passionate data scientists to help evolve the tools that support advisors and servicing agents in their interactions with clients.

As a Data Scientist on the Wealth Management Analytics Team, you will deliver data and insights that enable new capabilities and tools for our sales and servicing employees. You'll provide analyze data from platforms that support advisors in our remote advice channel, Chase branches, central offices, as well as their servicing desks. The wealth management industry is rapidly changing, and JPMorgan Chase is transforming our business to accelerate growth across the full wealth continuum. In this role you will be central in influencing the product strategy of our desktop tools as part of a cross-functional Product organization.

Job Responsibilities

• Analyze patterns of behaviors to uncover how advisors engage with existing desktop tools, diagnosing opportunities to improve workflows, and delivering new product capabilities that increase field productivity.
• Provide expertise as to how data visualization, data analysis, machine learning, and text analytics/NLP can be leveraged to uncover feature usage patterns, system gaps, potential performance enhancements, and other important patterns.
• Partner with Research and Design teams to diagnose client servicing pain points and re-imagine journeys across the client experience to drive product roadmaps
• Develop and launch a series of data-driven next best actions for our advisors to improve productivity and increase client satisfaction.
• Leverage Artificial Intelligence (AI) & Machine Learning (ML) to build new tools that drive meaningful change in the way Advisors and Service teams consume information

Required qualifications, capabilities, and skills:

• Bachelor's Degree and quantitative/statistical educational or professional experience required
• 'Jack of all trades' (or 'Jill of all trades') with a mix of business acumen, statistical know-how, and intuition to understand what is happening to data from inception to analytical output to business decision.
• Knowledge of statistics and a strong ability to effectively communicate design and results. You will need to be comfortable interacting with and persuading stakeholders (including 'data/math/statistics-phobic' types) with competing interests and accelerated timelines. Your advice will ultimately shape senior leaders' decision-making.
• Extensive querying (e.g., scripting against enterprise database systems), data cleaning, and programming skills - expertise in Python and SQL.
• Demonstrated experience applying descriptive, diagnostic, predictive, and prescriptive analytic techniques (including Machine Learning techniques) to deliver quantifiable business impact.
• Know when the "juice is worth the squeeze" - you stay abreast of new analytic techniques but can recognize and apply a more straightforward analytic approach when the question you are answering is less complex.

Preferred qualifications, capabilities, and skills:

• Bachelor's Degree and/or Master's Degree with a background in Social Science (Psychology, Economics, Political Science, Sociology, etc) or Humanities nice to have.
• Experience with Causal Inference (e.g. A/B Testing, Experimental Design and Quasi-Experimental Design).
• Previously worked in a data science function at a financial services firm or in consulting.
• Experience in a field-based sales environment with demonstrated success delivering insights to CRM systems such as Salesforce.
• Familiar with Business Intelligence (BI) tools (e.g. Tableau, Shiny Dashboards).
• Knowledge of data governance and ethical considerations in AI, ensuring compliance with industry standards and regulations.
• Human-centered data expert with an interest in eventual leadership.