Location: New York,NY, USA
Morgan Stanley Smith Barney, LLC seeks an Assistant Vice President, Corp. & Institutional Solutions in New York, New York
Assist in technology platform development efforts. Focus on enhancements of proprietary LeadIQ application to improve lead distribution, management, and oversight, and assist in expansion of
scope to additional business lines. Coordinate communications, support training efforts, and develop partnerships with Financial Advisor teams on use of platform and execution of reinvestment business. Work with data & analytics partners to develop monitoring and measurement framework to improve effectiveness of reinvestment efforts. Assist in producing quality presentations that provide visual storytelling with supporting details for management at various levels.
Salary: Expected base pay rates for the role will be between $135,000 and $135,000 per year at the commencement of employment. However, base pay if hired will be determined on an individualized basis and is only part of the total compensation package, which, depending on the position, may also include commission earnings, incentive compensation, discretionary bonuses, other short and long-term incentive packages, and other Morgan Stanley sponsored benefit programs.
Requirements:
Requires a Bachelor's degree in Finance, Financial Engineering, or a related field of study and three (3) years of experience in the position offered or three (3) years as an Associate, Product Manager, Technology Manager or related occupation. Requires three (3) years of experience with: Product Management and strategy analysis in the financial technology industry; Developing and implementing product strategies for Fintech products; Market research; competitive analysis; business planning; Managing product integration through APIs; Designing, analyzing and interpreting results of experiments for product performance optimization; A/B testing, and data analysis; JIRA; MS Excel; MS PowerPoint; and SQL. Requires one (1) year of experience with: Migrating databases from on-prem to cloud-based data warehouses, including Snowflake, and data architecture principles; Designing end-to-end machine learning systems, including identification of business objectives, feature layouts and selection, model testing, and continuous monitoring; Dataiku; Snowflake; Tableau; and Thinkcell.
Qualified Applicants:
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