Data Scientist - Wealth Management

Description

Leverage your technical expertise to shape innovative solutions and align capabilities to solve real-world challenges!

As a Data Science Associate on the Online Investing Data Science Team for US Wealth Management (“USWM”), your ability to blend cross-functional knowledge in Online Investing, 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.

Job Responsibilities:

Analyze client, macro-behavioral trends as it relates to Online Investing, financial products and solutions that are offered on JPMorgan’s USWM platform

Provide analytical support for Online Investing strategy and platform engagement

Analyze client behavioral data to inform strategic decision making, including forming, investigating and researching hypotheses, as well as deep-dives into client deepening and retention efforts.

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 Online Investing, Finance, Legal and Data and Analytics.

Required qualifications, capabilities, and skills:

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

Preferred qualifications, capabilities, and skills:

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