This listing doesn't post a salary. Most similar roles pay
$126,800–$191,250.
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
1174 open roles
on FindRole.
As a Data Scientist, Auto Finance Data & Analytics - Sr. Associate, you will join the Auto Finance Data & Analytics team to transform digital behavior and performance data into actionable insights that shape strategy and improve conversion across the customer journey. You will work alongside Product, Technology, Design, and Risk partners to translate complex business questions into analytical solutions and machine learning models. Your daily responsibilities include conducting deep-dive analyses, developing predictive models using classification algorithms like random forest and gradient boosting, and refining measurement frameworks for senior leadership. You will utilize SQL, Python, Adobe Analytics, Tableau, and AI tools such as the LLM Suite and GitHub Copilot to solve problems in the auto finance space. The role focuses on analyzing the end-to-end digital customer engagement funnel to drive growth and improve conversion rates through data-driven storytelling.
What does a Data Scientist earn?
Median $162000 from 284 postings across 56 companies.
Translate complex business questions into analytical and AI/ML solutions for product teams.
Conduct deep-dive analyses to identify opportunities for product innovation and growth.
Develop and apply statistical models and machine learning algorithms to identify trends in complex data.
Analyze the end-to-end digital customer engagement funnel to improve conversion rates.
Create and refine measurement frameworks and KPIs to track performance and highlight anomalies.
Use AI tools and advanced analytics to accelerate analysis and drive strategic decision-making.
Communicate data-driven insights and recommendations to executive and technical stakeholders through clear storytelling.
What we're looking for
Three years of relevant experience in data science, machine learning, or a related field.
Experience translating digital customer behavior data into actionable insights and recommendations for business leaders.
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).
Ability to synthesize complex results and communicate recommendations to executive, business, and technical stakeholders.
Experience building conversational AI solutions and orchestrating machine learning services into an end-to-end application (preferred).
Amazon Web Services (AWS) Certified Cloud Practitioner certification (preferred).
Python
AWS
Machine Learning
Spark
SQL
H2O
Conda
Scala
R
Deep Learning
Sentiment Analysis
Time Series
Clustering
Classification
Big Data
Statistical Modeling