AI Scientist / Engineer (Data Science & Analytics)

PROLIM Global Corporation; Plano (TX); Hybrid; USD 120,000 - 155,000; Full time

Job summary

PROLIM Global Corporation in Plano, Texas, seeks an AI Scientist / Engineer with 5+ years in Data Science, Analytics or AI Engineering to design enterprise AI dashboards, build scalable data pipelines, and define adoption KPIs for value realization across a global organization.

Responsibilities include integrating data from cloud platforms, creating executive reports, collaborating with IT, Security, Finance, and business teams, and guiding governance of AI measurement frameworks.

Qualifications

• Bachelor's degree in Computer Science, Data Science, Analytics, Engineering, or related field; Master's preferred.
• 5 years of experience in Data Science, Data Analytics, Data Engineering, or AI Engineering.
• Experience building enterprise-scale dashboards using Power BI, Tableau, or similar visualization platforms.
• Strong SQL and Python programming skills.
• Experience integrating data from APIs, cloud platforms, data warehouses, and enterprise systems.
• Knowledge of AI/LLM platforms and usage metrics (prompts, tokens, credits, model utilization, API consumption, costs).
• Experience designing executive dashboards and KPI reporting.
• Strong understanding of data governance, data quality, and analytics best practices.
• Excellent communication skills with ability to translate complex analytics into executive insights.

Responsibilities

• Design and develop enterprise AI usage dashboards and executive scorecards across multiple AI platforms.
• Build scalable data pipelines to ingest, integrate, and transform AI usage, operational, and financial data from diverse enterprise systems.
• Develop KPIs and metrics for AI adoption, utilization, token consumption, credits, costs, ROI, and business value realization.
• Create executive-level visualizations and reports that support strategic decision-making and AI governance.
• Apply data science and statistical techniques to identify adoption trends, optimization opportunities, forecasting, and value realization insights.
• Collaborate with AI platform teams, IT, Security, Finance, Procurement, and business stakeholders to establish trusted enterprise AI metrics.
• Ensure data quality, governance, and consistency across enterprise AI reporting.
• Support AI portfolio management through cost optimization, utilization analysis, and performance monitoring.
• Recommend improvements to AI measurement frameworks, reporting standards, and executive dashboards.

Skills

Power BI

Tableau

SQL

Python

Data governance

Data analytics

Data engineering

Executive reporting

AI platforms

Communication

Education

Bachelor's degree

Master's degree preferred

Tools

Azure Synapse

Databricks

Snowflake

BigQuery

OpenAI APIs

Azure OpenAI

Job description

AI Scientist / Engineer (Data Science & Analytics)

Plano, Texas (Hybrid)

Description

We are seeking a highly motivated and experienced AI Scientist / Engineer with 5 years of experience in Data Science, Data Analytics, Data Engineering, or AI Engineering to join our dynamic AI Business Strategy & Value Realization team. This position is ideal for a candidate with strong expertise in enterprise analytics, AI platforms, data visualization, cloud technologies, and executive reporting, combined with the ability to transform complex data into actionable business insights. The successful candidate will be responsible for designing and operationalizing enterprise AI analytics capabilities, building scalable data pipelines and executive dashboards, developing AI adoption and ROI metrics, and delivering data-driven insights that enable strategic AI investment decisions, governance, cost optimization, and business value realization across a global organization.

Requirements

Essential Functions:

Key Responsibilities

• Design and develop enterprise AI usage dashboards and executive scorecards across multiple AI platforms.
• Build scalable data pipelines to ingest, integrate, and transform AI usage, operational, and financial data from diverse enterprise systems.
• Develop KPIs and metrics for AI adoption, utilization, token consumption, credits, costs, ROI, and business value realization.
• Create executive-level visualizations and reports that support strategic decision-making and AI governance.
• Apply data science and statistical techniques to identify adoption trends, optimization opportunities, forecasting, and value realization insights.
• Collaborate with AI platform teams, IT, Security, Finance, Procurement, and business stakeholders to establish trusted enterprise AI metrics.
• Ensure data quality, governance, and consistency across enterprise AI reporting.
• Support AI portfolio management through cost optimization, utilization analysis, and performance monitoring.
• Recommend improvements to AI measurement frameworks, reporting standards, and executive dashboards.

Minimum qualification:

• Bachelor''''s degree in Computer Science, Data Science, Analytics, Engineering, or a related field (Master''''s preferred).
• 5 years of experience in Data Science, Data Analytics, Data Engineering, or AI Engineering.
• Experience building enterprise-scale dashboards using Power BI, Tableau, or similar visualization platforms.
• Strong SQL and Python programming skills.
• Experience integrating data from APIs, cloud platforms, data warehouses, and enterprise systems.
• Knowledge of AI/LLM platforms and associated usage metrics (e.g., prompts, tokens, credits, model utilization, API consumption, costs).
• Experience designing executive dashboards and KPI reporting.
• Strong understanding of data governance, data quality, and analytics best practices.
• Excellent communication skills with the ability to translate complex analytics into executive-level insights.

Preferred Qualifications

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

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