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This listing doesn't post a salary. Most similar roles pay
$135,000–$195,000.
Based on 240 similar postings.
Employer
About JPMorgan Chase
JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.
JPMorgan Chase currently has
1243 open roles
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As a Data Scientist, Auto Finance Data & Analytics - Sr. Associate, you will join the Auto Finance Data & Analytics team to turn digital behavior and performance data into actionable insights. You will work with Product, Technology, Design, and Risk partners to build analytical solutions, guide strategic business decisions, and enable growth initiatives. Your daily responsibilities include conducting deep-dive analyses, developing predictive models, and refining measurement frameworks to improve conversion across the customer journey. You will utilize SQL, Python, and statistical concepts to perform data extraction and model development, while using tools like Adobe Analytics, Tableau, and GitHub Copilot. You will apply machine learning techniques, including logistic regression, k-nearest neighbors, random forest, and gradient boosting, to solve complex business problems and identify trends in digital customer engagement.
What does a Data Scientist earn?
Median $173200 from 329 postings across 64 companies.
Conduct deep-dive analyses to generate actionable insights and recommendations for product innovation and growth.
Present data-driven stories and recommendations to business leaders to guide strategic direction.
Develop and apply statistical analyses and mathematical models to identify trends in complex data.
Analyze the end-to-end digital customer engagement funnel to recommend improvements for conversion.
Evolve and refine measurement frameworks and key performance indicators to monitor product performance.
Implement data-driven strategies and models in partnership with Product, Technology, and Risk teams.
Leverage firm-approved AI tools to accelerate analysis and identify opportunities for innovation.
What we're looking for
Three years of relevant experience in data science, machine learning, or a related field.
Demonstrated experience translating digital customer behavior data into actionable insights and recommendations for business leaders.
Demonstrated experience defining key performance indicators, building measurement frameworks, and monitoring for anomalies in digital product performance.
Proficiency developing predictive models and applying classification algorithms like logistic regression, k-nearest neighbors, random forest, and gradient boosting.
Solid understanding of statistical concepts for data analysis and experience designing and evaluating A/B experiments.
Hands-on experience with SQL and Python for data extraction, analysis, and model development.
Experience using analytics and visualization tools such as Adobe Analytics and Tableau (or equivalent tools).
Strong ability to synthesize complex analytical results and communicate recommendations to executive, business, and technical stakeholders.
Experience building conversational artificial intelligence solutions and orchestrating machine learning services into an end-to-end application (preferred).
Amazon Web Services (AWS) Certified Cloud Practitioner certification (preferred).
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Tableau
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Python
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Statistical Modeling
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