Business Data Analyst III

Chickasaw Nation Industries, Inc.

1d•Remote

About The Position

The Business Data Analyst III 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. This position is remote. 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.

Requirements

Must possess appropriate level of certifications for this position as required by the contract.
Must be able to obtain and maintain the required customer clearance for access to systems, facilities, equipment and property.
Experience and proficiency with Power BI
Experience with reporting/preparing presentations
Bachelor's degree and a minimum of four to seven (4-7) years of relevant experience, or equivalent combination of education/experience.

Nice To Haves

Experience with Looker Studio
Experience with Tableau
Experience with R
Experience with Python

Responsibilities

Serves as the primary analytics partner for Business Development, Pricing, Proposal, Finance, Accounting, and Operations.
Ensures adequate control of key business metrics.
Builds automated dashboards and self-serve reporting (e.g., Looker Studio/Power BI/Tableau).
Designs and evaluates A/B tests; measure causal impact and ROI of initiatives.
Collects, cleans, and analyzes large datasets using statistical techniques and data mining tools.
Identifies 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 business stakeholders to understand their data needs and requirements.
Translates business questions into data analysis tasks and develop appropriate methodologies to answer those questions.
Ensures 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 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.
Provides recommendations based on data analysis to support strategic decision-making within the organization.
Contributes to the development and implementation of data governance policies and procedures.
Ensures compliance with data privacy regulations and best practices for data management.
Stays updated with industry trends, emerging technologies, and best practices in data analysis.
Continuously seeks opportunities to improve data analysis processes, tools, and methodologies.
Collaborates with cross-functional teams, including business stakeholders, IT teams, and management, to understand data requirements and effectively communicate findings.
Ability to present, explain and justify complex data analysis concepts in a clear and understandable manner.
Provides training and support to end-users on data analysis tools, techniques, and best practices.
Assists in building data literacy within the organization.