Data Analytics Analyst, PAYS $68/HR

Added: June 6, 2022
  • Country: United States
  • Region: Indiana

Data Analytics Analyst needs 2+ years of work experience with data analytics or data science
Data Analytics Analyst requires:
 Bachelor’s degree or higher in any of Data Science, Math, Statistics, Computer Science, Information Technology, or related field.
 1+ years of work experience within the Financial Services sector.
 Thorough understanding of ITIL/ITSM processes / ITIL v3 or v4 Foundations Certification.
 Working knowledge of Snowflake or similar data warehouse architecture.
 Experience in business intelligence or CX.
 Experience in operations research, data science, machine learning, or deep learning.
 Experience with time series forecasting or anomaly detection.
 Experience with CI/CD, alerting, or MLOps.
 Must be skilled in the use of SQL, able to write queries.
 Must be proficient in the workings of data technologies.
 Extensive experience working with business intelligence and data visualization tools.
 Industry experience solving business problems through application of innovative data and analytics approaches and emerging technologies.
 Familiarity with data structures, big-data concepts, cloud computing, open-source tools and optimization techniques.
Data Analytics Analyst duties:
 Partner with Technology peers to identify key metrics that will effectively measure & communicate Technology performance and increase business value.
 Extract, filter, and aggregate data through tools, queries, and programming languages.
 Ensure data is captured, models are built, metrics are computed, and charts/dashboards are available in real time. Present data from various perspectives / slices / categories.
 Develop visualization of analysis in formats such as tables, charts, graphs, heat maps and other report types.
 Utilize business intelligence and data visualization software to create reports and presentations for key stakeholders. These reports must be engaging, clear, concise, and tailored in such a manner that will suit and appeal to the audience at hand.
 Identify correlations, patterns, and trends in disparate data sources.
 Organize and transform data into comprehensible structures.
 Perform statistical analysis.
 Solve challenging analytical problems.
 Define requirements for other development & technology teams to fulfill (such as capturing additional data in logs / databases / warehouses) in order to make new data available for analysis & reporting.
 Identify questions to be answered and define appropriate analytics models. Prepare relevant data sources for analysis.


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