Performs data analysis and research using SQL/R and Python. Identifies data issues and performs root cause analysis to improve data quality in a timely manner. Participates in data management projects to improve the quality of the data. Monitors the helpdesk queue and logging incidents. Defines and executes test plans and supports user acceptance testing for process enhancements. Utilizes research tools to procure company specific data and perform data analysis. Assists in documentation and transition of new areas of work, while maintaining and updating procedural documents.

Primary Responsibilities:

Proposes process enhancements for the efficient, accurate, and timely completion of all activities operation tasks and helpdesk requests. Analyzes information obtained from management to conceptualize and define operational problems. Studies and analyzes information about alternative courses of action to determine which plan will offer the best outcomes. Presents the results of mathematical modeling and data analysis to management or other end users. Observes the current system in operation. Gathers and analyzes information about each of the current system parts of component problems, using a variety of sources.

Education and Experience:

Bachelor's degree (or foreign education equivalent) in Computer Science, Engineering, Information Technology, Information Systems, Mathematics, Physics, or a closely related field and three (3) years of experience as a Manager, Data Analytics and Insights (or closely related occupation) performing data analysis and research using SQL/R and Python.

Or, alternatively, Master's degree (or foreign education equivalent) in Computer Science, Engineering, Information Technology, Information Systems, Mathematics, Physics, or a closely related field and one (1) year of experience as a Manager, Data Analytics and Insights (or closely related occupation) performing data analysis and research using SQL/R and Python.

Skills and Knowledge:

Candidate must also possess:

Demonstrated Expertise ("DE") analyzing large-scale data to detect patterns, trends, and nuances; gathering data from disparate sources; and simplifying data loading by designing clean data models and setting up ETL pipelines, using data querying, modeling, and ETL tools -- SQL Server, and Toad Modeler. DE extracting, transforming, and analyzing unstructured and semi-structured data -- text content (onsite articles), customer-entered feedback (surveys and online tool interactions), and email engagement activity -- to generate insights for content strategy and customer experience touchpoints, using data mining tools (R, Python, and Oracle SQL Developer). DE planning, designing, and implementing diverse BI dashboards using querying tools to visualize the data; and querying and analyzing data to produce insights -- Qlik view, Qlik Sense, Power BI, and MS Excel -- using BI dashboards. DE parsing, summarizing, and visualizing portfolio journeys across on and offline activity; tying engagements to financial transactions using investment data; and performing statistical analysis, and data extraction, transformation, and summarization to support and inform client service strategies within the financial services industry, using inferential statistics, hypothesis testing, experiment design, and Cloud technologies.

Salary: $101,075.00 - $121,700.00 /year.