Data Scientist Associate

JPMorgan Chase • Columbus, OH

93d

About The Position

Leverage your technical expertise to shape innovative solutions and align capabilities to solve real-world challenges! As a Data Science Associate on the Solutions and Advice Data Science Team for US Wealth Management ("USWM"), your ability to blend cross-functional knowledge in financial products, markets, statistics and advanced analytics will be a key to your success. You'll utilize strong communication skills to effectively operate in direct collaboration with key stakeholders across functions and lines-of-business.

Requirements

• 1+ years of experience working in an analytical, data science, finance or management/economic consulting role.
• BS Degree in a related field, such as Mathematics, Statistics, Engineering, Computer Science, Finance, Economics or other applicable STEM discipline.
• Adept at explaining and converting complex concepts into digestible information to be consumed by audiences at various levels of the business.
• Strong storytelling capabilities.
• Aptitude for learning new theory and new technology.

Nice To Haves

• Masters Degree or PhD.
• Knowledge or demonstrable interest in financial securities and markets.
• Practical understanding of advanced statistics, econometrics and / or machine learning.
• Practical understanding of financial modeling and economics.
• Knowledge or demonstrable experience in Python, SQL and /or R.

Responsibilities

• Analyze client, advisor and macro-behavioral trends as it relates to financial products and solutions that are offered on JPMorgan's USWM platform (e.g., managed solutions, mutual funds, ETFs, banking, and lending).
• Provide analytical support for regulatory matters.
• Analyze financial flow data to inform strategic decision making, including forming, investigating and researching hypotheses, as well as deep-dives into competitor's strategic positioning.
• Use a variety of data tools and technologies, including industry-standard and open-source platforms, to assemble, organize and analyze data, including Python, R and SQL.
• Apply statistical, causal inference and machine learning modeling methods and techniques, including clustering algorithms, tree-based models, matching methods and time-series anomaly detection.
• Present findings to key stakeholders, including senior leaders, across Solutions & Advice, Finance, Legal and Data and Analytics.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Industry: Credit Intermediation and Related Activities
• Education Level: Bachelor's degree