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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI / ML Data Analyst - **Company:** Randstad - **Location:** Charlotte, NC, United States - **Experience:** Experienced - **Salary:** $84,656.0 - $105,456.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Data Analysis, Software Applications, Microsoft Azure, Big Data, Information Systems, Information Engineering, Data Visualization, Machine Learning, Power BI, Tensorflow, SQL Databases, Tableau (Software), Microsoft Power Automate, Pytorch, Large Language Models, Prompt Engineering, Generative AI, Scikit Learn, Information Technology, Data Analytics, Tools for Reporting - **Published:** August 12, 2026 - **Apply:** https://www.dice.com/job-detail/c276a96c-9d1e-434f-a045-4cba7610c2c6 ## About the Role We are seeking a highly motivated Data Analyst with strong analytical skills and practical knowledge of Artificial Intelligence (AI), Machine Learning (ML), and Data Analytics to transform data into actionable business insights. The ideal candidate will leverage traditional analytics techniques along with AI-driven tools and automation to support strategic decision-making, improve operational efficiency, and drive business outcomes., * Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, Information Systems, Engineering, or a related field. * 3+ years of experience in Data Analytics, Business Intelligence, or related disciplines. * Experience with Power BI, Tableau, or similar visualization tools. * Solid understanding of statistical analysis and data modeling. * Strong problem-solving and communication skills. * Knowledge of Machine Learning concepts and predictive analytics. * Experience with AI/ML libraries such as Scikit-Learn, TensorFlow, or PyTorch. * Familiarity with Generative AI platforms and Large Language Models (LLMs). * Experience using AI-assisted analytics tools such as Microsoft Copilot, Azure AI, OpenAI APIs, or similar technologies. * Understanding of prompt engineering and AI-driven data exploration. * Knowledge of AI governance, responsible AI practices, and data privacy considerations. * - May collaborate with programmers to coordinate delivery of software application. * - Routine accountability is for technical knowledge and capabilities. Works under minimal supervision, with general guidance from more seasoned consultants. qualifications: Collect, analyze, and interpret large datasets from multiple internal and external sources., Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, Information Systems, Engineering, or a related field. 3+ years of experience in Data Analytics, Business Intelligence, or related disciplines. Experience with Power BI, Tableau, or similar visualization tools. Solid understanding of statistical analysis and data modeling. Strong problem-solving and communication skills. Knowledge of Machine Learning concepts and predictive analytics. Experience with AI/ML libraries such as Scikit-Learn, TensorFlow, or PyTorch. Familiarity with Generative AI platforms and Large Language Models (LLMs). Experience using AI-assisted analytics tools such as Microsoft Copilot, Azure AI, OpenAI APIs, or similar technologies. Understanding of prompt engineering and AI-driven data exploration. Knowledge of AI governance, responsible AI practices, and data privacy considerations. - May collaborate with programmers to coordinate delivery of software application. - Routine accountability is for technical knowledge and capabilities. Works under minimal supervision, with general guidance from more seasoned consultants. skills: APIs,Artificial Intelligence (AI),AI-driven tools,AI and Machine Learning,AI,large datasets,data exploration,Data Analytics,visualization tools,Generative AI,Data Engineering,Information Systems,Computer Science,Large Language Models,LLMs,Machine Learning,Machine Learning concepts,Azure,Microsoft Copilot,Power BI,prompt engineering,PyTorch,SQL queries,ML libraries,Scikit-Learn,software application,Tableau,TensorFlow,analytics tools,strong analytical skills,communication skills,leadership,highly motivated,proactively,minimal supervision,analytical solutions,automation,operational efficiency,actionable business insights,Business Intelligence,key business metrics,assessments,responsible AI practices,dashboards,responsible AI,data models,data modeling,data privacy,data quality,Data Science,AI governance,Mathematics,Statistics,statistical analysis,predictive analytics,risks,strategic decision-making,technical knowledge,identify trends,visualizations ## Description * Collect, analyze, and interpret large datasets from multiple internal and external sources. * Design, develop, and maintain dashboards, reports, and visualizations using tools such as Power BI, Tableau, or similar platforms. * Utilize AI and Machine Learning techniques to identify trends, predict outcomes, and uncover business opportunities. * Develop and optimize SQL queries and data models to support reporting and analytics needs. * Perform data quality assessments, validation, and cleansing activities. * Partner with business stakeholders to understand requirements and translate them into data-driven solutions. * Use Generative AI and advanced analytics tools to automate reporting, insights generation, and data exploration. * Monitor key business metrics and proactively identify risks, anomalies, and improvement opportunities. * Collaborate with Data Engineering, Product, Technology, and Business teams to implement analytical solutions. * Present findings and recommendations to senior leadership and stakeholders., Design, develop, and maintain dashboards, reports, and visualizations using tools such as Power BI, Tableau, or similar platforms. Utilize AI and Machine Learning techniques to identify trends, predict outcomes, and uncover business opportunities. Develop and optimize SQL queries and data models to support reporting and analytics needs. Perform data quality assessments, validation, and cleansing activities. Partner with business stakeholders to understand requirements and translate them into data-driven solutions. Use Generative AI and advanced analytics tools to automate reporting, insights generation, and data exploration. Monitor key business metrics and proactively identify risks, anomalies, and improvement opportunities. Collaborate with Data Engineering, Product, Technology, and Business teams to implement analytical solutions. 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