Asset Management Research Technology - Data Science Analytics Team Lead - Executive Director Asset Management Research Technology - Data  …

J.P.Morgan
à Londres, Angleterre, Royaume-Uni
CDI, Plein-temps
Dernière candidature, 17 juin 21
Competitive
J.P.Morgan
à Londres, Angleterre, Royaume-Uni
CDI, Plein-temps
Dernière candidature, 17 juin 21
Competitive
JPMorgan is one of the world’s largest asset managers with over $2 trillion in Assets Under Management.  At the heart of Asset Management’s investment process is proprietary fundamental and quantitative research.  The Research Technology within Asset Management Technology builds the technology platforms that underpin our

JPMorgan is one of the world’s largest asset managers with over $2 trillion in Assets Under Management.  At the heart of Asset Management’s investment process is proprietary fundamental and quantitative research.  The Research Technology within Asset Management Technology builds the technology platforms that underpin our research efforts globally.  Within Research Technology, the Data Science Analytics Tech team has a mission to deliver high quality, production-grade Data Science-based analytics & generic capabilities to consumers across the Investment Platform.

AM Research Technology is seeking a highly talented individual to lead the Data Science Analytics team.  In this role the individual will partner with Data Scientists and stakeholders to deliver Data Science-based analytics and capabilities throughout Asset  Management.  Responsibilities include building and operating highly sophisticated end-to-end data pipelines, setup of production infrastructure on AWS, production model serving, as well as API and data delivery mechanisms for consumers.  This individual will be leading a team of currently five outstanding engineers.  The role reports to the Head of Research Technology.  This is a huge opportunity for an individual to have a major impact across all of Asset Management.

Requirements:

·         Significant Software Engineering experience

·         Strong experience architecting, developing, and operating within AWS

·         AWS Solutions Architect certification strongly preferred

·         Proficiency in Python programming

·         Proficiency with Python libraries commonly used in Data Science

·         Commercial experience deploying AI/ML solutions to production

·         Significant knowledge of AI/ML techniques, including NLP

·         Experience building robust data pipelines for both structured and unstructured data

·         Experience with Spark and/or other Big Data frameworks

·         Experience with developing APIs used by other teams

·         Familiarity with financial / investment concepts

·         Experience managing small teams with focus on the career development of their team members

·         Experience working with Data Scientists and highly knowledgeable of their workflows

·         Skilled in managing stakeholder expectations

·         Highly collaborative

·         Proven ability to iterate quickly



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