Business Data Analyst at Chickasaw Nation Industries
Washington, DC 20004, USA -
Full Time


Start Date

Immediate

Expiry Date

15 Oct, 25

Salary

85000.0

Posted On

16 Jul, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Access, Sql, Data Analysis

Industry

Information Technology/IT

Description

The Business Data Analyst II is responsible for analyzing and interpreting data to provide insights and support decision-making within an organization. Works with large datasets, performs statistical analysis, and creates reports or visualizations to communicate findings .
Chickasaw Nation Industries, Inc. serves as a holding company with multiple subsidiaries engaged in several lines of business (Technology, Infrastructure & Engineering, Health, Manufacturing, Public Safety, Consulting, and Transportation) for the federal government and commercial enterprises. A portion of our profits is used to support Chickasaw citizens. We are proud to support the economic development and long-term viability of the Chickasaw Nation and its people. CNI offers premium benefits eligible on the first day of hire to full time employees; (Medical - Dental – Vision), Company Life Insurance, Short-Term and Long-Term Disability Insurance, 401(K) Immediate Vesting, Professional Development Assistance, Legal Aid Assistance Program, Family Planning / Fertility Assistance, Personal Time Off, and Observance of Federal Holidays.
As a federal contractor, CNI is a drug-free workplace and adheres to the Federal Controlled Substance Act.

ESSENTIAL REQUIREMENTS

  • Must be able to obtain and maintain the required customer clearance for access to systems, facilities, equipment and property .
  • Experience with data analysis using tools such as MS Excel, Power BI Power Apps, Power Automate, SQL
  • Must possess appropriate level of certifications for this position as required by the contract.

EDUCATION AND EXPERIENCE

Bachelor’s degree and a minimum of five (5) y ears of relevant experience with data analysis using tools such as MS Excel, Power BI Power Apps, Power Automate, SQL , or equivalent combination of education/experience.

Responsibilities

KEY DUTIES AND RESPONSIBILITIES

Essential D uties and responsibilities include the following . Other duties may be assigned.

  • Collects, cleans, and analyzes large datasets using statistical techniques and data mining tools. Helps to identify trends, patterns, and correlations in the data to extract meaningful insights that can drive business decisions.
  • Creates visualizations, dashboards, and reports to present data findings in a clear and concise manner. Uses tools such as Tableau, Power BI, or Excel to create visual representations of data that can be easily understood by stakeholders.
  • Collaborates with supervisors, business stakeholders to understand their data needs and requirements. Translates business questions into data analysis tasks and develop appropriate methodologies to answer those questions.
  • Assists with the accuracy, completeness, and reliability of data by performing data validation and quality checks.
  • Identifies data anomalies or inconsistencies and work with relevant teams to resolve issues. Communicates findings to supervisors, stakeholders and assist in developing action plans based on the insights gained from the data.
  • Applies simple statistical techniques such as regression analysis, hypothesis testing, clustering, or segmentation to uncover insights from the data. Uses statistical software such as R or Python to perform advanced analytics.
  • Contributes to the development and implementation of data governance policies and procedures. Ensures compliance with data privacy regulations and best practices for data management
  • S tays updated with industry trends, emerging technologies, and best practices in data analysis. C ontinuously seek s opportunities to improve data analysis processes, tools, and methodologies.
  • C ollaborates with cross-functional teams, including business stakeholders, IT teams, and management, to understand data requirements and effectively communicate findings. P resent s complex data analysis concepts in a clear and understandable manner.
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