Morgan Stanley Services Group, Inc. seeks an Associate, Institutional Securities Techin New York, New York
Design, plan, and execute on Investment Banking and Global Capital Market technology department projects to meet specific client needs. Apply strategic, analytical, and data science skills to challenges faced by business users. Perform data analysis and use analytics tools. Conduct modern data mining, quantitative research, and data science techniques. Conduct fundamental analyses and financial modeling, including using Excel for building and maintaining financial models. Define analytical agenda for projects including framing ambiguous business questions into analytical plans and executing these plans with precision. Assessing data needs, sourcing files, preparing data, creating new features, and evaluating quality.
Salary: Expected base pay rates for the role will be between $153,000 and $153,000 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 Master's degree in Business Analytics, Computer Science, Data Science, or a related field of study and three (3) years of experience in the position offered or three (3) years as a Data Scientist, Software Engineer, or related occupation in the technology field. Requires three (3) years of experience with: Programming Languages including Python, and R; Statistics; Predictive and Descriptive analytics; Machine learning; Data Visualization including Tableau; Python Tools and Libraries including Scikit Learn; Communicating findings to larger audiences and working with cross functional teams; SQL Programs including Microsoft SQL, Azure SQL, and DB2; Data providers and products including Experian and Equifax; Data mining; Data wrangling and ETL knowledge. Requires one (1) year of experience with: Databricks; Power BI; Big Data including Hadoop and Spark; Cloud computing including Azure; Snowflake; Teradata; TOAD, DB Artisan; Tensor Flow; Working in Financial Services or FinTech; Version Control including GIT; Experimental Design including A/B testing.
Qualified Applicants:
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