JPMorgan AWM Finance Data Science AI/ML Associate 

United States, New Jersey, Jersey City 

158602613

As a Data Scientist AI/ML Engineer within Asset and Wealth Management, you will be collaborating closely with various teams to prototype, build, test and deploy a large scale federated LLM platform. You will work with an agile team that will work on building, and delivering trusted market-leading technology products in a secure, stable, and scalable way. You will partner with our Global Data Science teams to design, develop, deploy and operate machine learning driven applications and data pipelines.

As part of our MIS and Platforms team, you will play a crucial role in defining, refining, and delivering set goals for our firm. You will work closely with product owners and teams to identify strategic solutions and implement various exploratory data analysis techniques. Your expertise in data mining, visualization, and storytelling will make a significant impact on the business. Additionally, you will employ scaling and automation techniques to data preparation and transform model outputs into formats that are easily digestible to end users.

Required Qualifications, Capabilities, and Skills:

• 8+ years of experience in data-related projects and 5+ years of experience in data science.
• Bachelor's degree in Data Science, Computer Science, or Engineering. Different fields of study with significant professional experience in BI and Analytics Development are also acceptable.
• Hands on involvement in building and operating highly sophisticated LLM driven applications.
• Partnering directly with other technology teams on LLM projects to advise and assist as needed.
• Collaborating with Data Science to deliver state of the art ML products.
• Ability to use pertinent data and facts to identify and solve a range of problems within the area of expertise.
• Experience in Cloud and Big Data platforms such as AWS, Databricks, Snowflake, Hive, Pig, Apache Spark, etc.
• Mandatory experience in exploratory and regression data analysis.
• Hands-on experience with pandas and PySpark/PySQL stack, including building data extraction pipelines.
• Strong skills in statistics, exploratory data analysis, and machine learning.
• Proficiency in data querying using SQL (Snowflake, Databricks) and Python (packages and libraries like Scikit, Keras, Pandas, PySpark/PySQL).

Preferred qualifications, capabilities, and skills:

• Good communication and analytical skills.
• Self-starter with attention to detail and results-oriented mindset, able to work under minimal guidance.
• Working proficiency in data visualization tools, including experience with BI technologies such as Tableau.
• Strong mathematical and inferential statistics skills.
• Experience in end-to-end implementation of Business Intelligence (BI) reports and dashboards.