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.