Business Analyst
OculusIT, Houston, TX, United States
The Business Analyst for the O-EYE platform plays a critical role in building and managing the data foundation that powers analytics, reporting, and AI-driven insights. This role focuses on extracting, transforming, and structuring data from diverse university systems and client environments to enable benchmarking, decision support, and intelligent automation.
· The position sits at the intersection of data, analytics, and AI, supporting the development of a unified intelligence layer across institutional systems.
Key Responsibilities:
1. Data Acquisition & Integration
Extract and consolidate data from multiple sources including Student Information Systems (SIS), CRM platforms, application systems, and operational tools
Support ingestion of data into centralized data lake or warehouse environments
Ensure data consistency, normalization, and traceability across sources
Work with technical teams to streamline data pipelines and ingestion processes.
Clean, transform, and standardize raw datasets for analytical use
Design and maintain data models aligned with reporting, benchmarking, and AI use cases
Develop reusable and scalable datasets for ongoing analysis and dashboards
Ensure data integrity, governance, and documentation standards.
3. Analytics & Insights
Conduct exploratory data analysis to identify trends, patterns, and anomalies
Support cross-institutional and departmental benchmarking initiatives
Generate actionable insights to inform operational and strategic decision‑making
Translate business questions into analytical frameworks.
Develop dashboards, reports, and visualizations for business and executive stakeholders
Present complex data in a clear, concise, and consumable format
Enable KPI tracking, performance monitoring, and outcome measurement
Continuously improve reporting frameworks based on stakeholder feedback.
5. AI Enablement
Prepare structured and high-quality datasets for AI/ML models and LLM-based applications
Collaborate with AI and engineering teams on prompt engineering and data pipelines
Ensure data readiness and quality to support reliable AI-driven outputs
Contribute to the evolution of O-EYE’s intelligence and automation capabilities.
Required Skills & Qualifications:
Technical Skills:
Strong proficiency in SQL for data extraction and manipulation
Experience with Python (pandas, NumPy, or equivalent data processing libraries)
Familiarity with data visualization tools such as Power BI, Tableau, or similar
Understanding of ETL processes, data pipelines, and data lake/warehouse architectures
Exposure to cloud-based data environments is a plus.
Analytical Skills:
Strong problem‑solving and critical thinking abilities
Ability to work with incomplete, inconsistent, or complex datasets
High attention to detail with a focus on data quality and accuracy
Ability to derive meaningful insights from large datasets.
Ability to work cross‑functionally with technical, functional, and business teams
Support Solution Architects and AI teams with structured data inputs
Strong communication skills to translate data insights into business context
Comfortable working in a fast‑paced, evolving project environment
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· The position sits at the intersection of data, analytics, and AI, supporting the development of a unified intelligence layer across institutional systems.
Key Responsibilities:
1. Data Acquisition & Integration
Extract and consolidate data from multiple sources including Student Information Systems (SIS), CRM platforms, application systems, and operational tools
Support ingestion of data into centralized data lake or warehouse environments
Ensure data consistency, normalization, and traceability across sources
Work with technical teams to streamline data pipelines and ingestion processes.
Clean, transform, and standardize raw datasets for analytical use
Design and maintain data models aligned with reporting, benchmarking, and AI use cases
Develop reusable and scalable datasets for ongoing analysis and dashboards
Ensure data integrity, governance, and documentation standards.
3. Analytics & Insights
Conduct exploratory data analysis to identify trends, patterns, and anomalies
Support cross-institutional and departmental benchmarking initiatives
Generate actionable insights to inform operational and strategic decision‑making
Translate business questions into analytical frameworks.
Develop dashboards, reports, and visualizations for business and executive stakeholders
Present complex data in a clear, concise, and consumable format
Enable KPI tracking, performance monitoring, and outcome measurement
Continuously improve reporting frameworks based on stakeholder feedback.
5. AI Enablement
Prepare structured and high-quality datasets for AI/ML models and LLM-based applications
Collaborate with AI and engineering teams on prompt engineering and data pipelines
Ensure data readiness and quality to support reliable AI-driven outputs
Contribute to the evolution of O-EYE’s intelligence and automation capabilities.
Required Skills & Qualifications:
Technical Skills:
Strong proficiency in SQL for data extraction and manipulation
Experience with Python (pandas, NumPy, or equivalent data processing libraries)
Familiarity with data visualization tools such as Power BI, Tableau, or similar
Understanding of ETL processes, data pipelines, and data lake/warehouse architectures
Exposure to cloud-based data environments is a plus.
Analytical Skills:
Strong problem‑solving and critical thinking abilities
Ability to work with incomplete, inconsistent, or complex datasets
High attention to detail with a focus on data quality and accuracy
Ability to derive meaningful insights from large datasets.
Ability to work cross‑functionally with technical, functional, and business teams
Support Solution Architects and AI teams with structured data inputs
Strong communication skills to translate data insights into business context
Comfortable working in a fast‑paced, evolving project environment
#J-18808-Ljbffr