Data Scientist Associate

Description

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.

Job 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.

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.

Knowledge or demonstrable experience in Python, SQL and /or R.