Morgan Stanley Smith Barney, LLC seeks an Assistant Vice President in Jersey City, New Jersey
Leverage predictive machine learning modeling and algorithms to deliver on use cases for wealth management across personalization, marketing, digital and products strategy. Build statistical modeling solutions at speed and scale to solve business problems. Responsible for the development of data science and modeling capabilities in the cloud transformation journey. Develop data science solutions that can be tested and deployed to enable data-driven recommendations and outcomes. Implement and scale-up high-availability models and algorithms for various company business and corporate functions. Investigate and create experimental prototypes that work on specific domains and verticals. Analyze large, complex data sets to reveal underlying patterns, correlations and trends quantitatively. Support and enhance existing models to ensure better performance. Set up and conduct large-scale experiments to test hypotheses and drive business growth.
Salary: Expected base pay rates for the role will be between $158,000 and $158,000 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 PhD in Data Science, Geophysical Sciences, Statistics, Mathematics, or a related field of study and two (2) years of experience in the position offered or two (2) years as a Data Scientist, Statistician, or a related occupation.
Requires two (2) years of experience with: developing end-to-end machine learning systems including identification of business objectives, feature engineering and selection, model deployment in a production environment and continuous monitoring; model deployment and systems integration through APIs; designing, analyzing and interpreting the results of experiments to optimize product performance with A/B testing; Python; SQL; developing and deploying models on cloud platforms including AWS or Azure; Tableau; and developing predictive models in consumer-oriented financial industry such as credit cards, asset management, or related. Requires any amount of experience with: publishing peer-reviewed scientific papers with applications of data science or machine learning methods.
Qualified Applicants:
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