QA Data Analyst

Akkodis is seeking a QA Data Analyst for a Contract with a client in Cupertino, CA/Sunnyvale, CA(Hybrid). You will be responsible for analyzing, cleaning, and validating large datasets to ensure accuracy and reliability of insights.

Rate Range: $55/hour to $60/hour;
The rate may be negotiable based on experience, education, geographic location, and other factors.

• Analyze and validate large datasets to ensure accuracy, consistency, and completeness.
• Interpret and validate machine learning models to confirm reliability and performance (no model building required).
• Perform data cleaning and transformation to prepare data for analysis and reporting.
• Develop and maintain advanced Excel reports for data tracking, analysis, and visualization.
• ate with cross-functional teams to support data-driven decision-making and quality assurance processes.
• Utilize data visualization tools such as Tableau or Power BI to present insights effectively (good to have).

• Bachelor’s degree in data science, Statistics, Computer Science, or a related field.
• Minimum 5–6 years of experience in data analysis and validation.
• Advanced proficiency in Excel and strong experience with data cleaning and validation.
• Ability to interpret and validate machine learning models (no model building required).

If you are interested in this role, please apply. For other opportunities or questions, contact  Pay Details: $55.00 to $60.00 per hour

Benefit offerings available for our associates include medical, dental, vision, life insurance, short-term disability, additional voluntary benefits, EAP program, commuter benefits and a 401K plan. Our benefit offerings provide employees the flexibility to choose the type of coverage that meets their individual needs. In addition, our associates may be eligible for paid leave including Paid Sick Leave or any other paid leave required by Federal, State, or local law, as well as Holiday pay where applicable.

Equal Opportunity Employer/Veterans/Disabled

Military connected talent encouraged to apply

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