AI Scientist / Engineer (Data Science & Analytics)

Cinter Career•Plano, TX

1d•Onsite

About The Position

The AI Scientist / Engineer will develop and implement data-driven analytics solutions supporting AI adoption, operational efficiency, and business decision-making. The role focuses on enterprise data analytics, AI platforms, data engineering, and business intelligence to deliver actionable insights and measurable business value. The position calls for a strong background in data science, analytics, and cloud technologies, including hands-on experience building scalable data pipelines, executive dashboards, and performance reporting solutions. The role collaborates with technical and business teams to support AI initiatives, data governance, and strategic decision-making.

Requirements

Bachelor's degree in Computer Science, Data Science, Analytics, Engineering, or a related field, or equivalent practical experience.
5+ years of professional experience in Data Science, Data Analytics, Data Engineering, AI Engineering, or related technical roles.
Strong programming skills in SQL and Python for data analysis, automation, and data processing.
Hands-on experience developing enterprise dashboards and business intelligence solutions using Power BI, Tableau, or similar platforms.
Experience designing and implementing data pipelines, ETL/ELT processes, and data integration solutions.
Experience working with APIs, cloud platforms, data warehouses, and enterprise data systems.
Understanding of AI/LLM platforms and usage metrics, including tokens, API consumption, model utilization, and associated costs.
Experience developing KPIs, executive dashboards, and performance reporting frameworks.
Strong knowledge of data governance, data quality, and analytics best practices.
Strong analytical, problem-solving, and data visualization skills.
Excellent communication and collaboration skills, with the ability to present complex data insights to technical and non-technical stakeholders.

Nice To Haves

Experience with enterprise AI platforms such as Azure AI, Microsoft Copilot, Azure OpenAI, AWS AI services, or Google Vertex AI.
Familiarity with cloud data platforms such as Microsoft Fabric, Azure Synapse, Databricks, Snowflake, or BigQuery.
Experience measuring AI adoption, ROI, business value realization, or technology investment performance.
Knowledge of FinOps, AI governance, and enterprise technology portfolio management.
Experience supporting executive leadership through strategic analytics and business performance reporting.

Responsibilities

Design, develop, and maintain enterprise AI analytics dashboards, business intelligence reports, and executive scorecards.
Build and optimize scalable data pipelines to collect, integrate, and transform data from multiple enterprise systems and AI platforms.
Develop and monitor KPIs related to AI adoption, utilization, costs, ROI, and business performance.
Analyze AI usage data, including token consumption, API utilization, platform costs, and operational metrics.
Apply data science, statistical analysis, and forecasting techniques to identify trends, optimization opportunities, and business insights.
Create interactive data visualizations and executive-level reports using Power BI, Tableau, or similar tools.
Collaborate with IT, AI engineering, Finance, and business stakeholders to establish reliable analytics and reporting solutions.
Ensure data accuracy, consistency, quality, and compliance with data governance standards.
Support AI investment analysis, cost optimization, and performance monitoring through data-driven insights.
Develop and improve analytics frameworks, reporting processes, and data visualization standards.
Translate complex technical data into clear, actionable recommendations for business and executive stakeholders.
Stay current with emerging AI technologies, cloud data platforms, and analytics best practices.