The Data Analyst transforms raw academic documents and course datasets into clean, reliable, and actionable information. This role ensures near-perfect accuracy of transcript extraction and course catalog data to support the Human-in-the-Loop (HITL) Maker/Checker Pod, Transfer Credit Evaluation (TCE) workflows, and the PROSPECT Course Co-Pilot. The analyst combines data processing, quality assurance, and analytical skills to improve AI outputs and enable strong academic-mapping products for customers.
Responsibilities
- Conduct end-to-end data processing for transcripts and academic records, ensuring 99%+ accuracy as part of the HITL model.
- Review, validate, and correct AI-generated extractions to meet customer SLAs and prevent churn.
- Support the creation, maintenance, and optimization of datasets used for TCE and PROSPECT operations.
- Scrape, structure, and standardize course catalog data for use in the Course Co-Pilot model.
- Develop reporting dashboards that monitor accuracy rates, processing times, and dataset quality.
- Participate in the design of data workflows to improve efficiency and quality control.
- Identify data trends, anomalies, and opportunities for product or process improvements.
- Work closely with Professional Services, Product, and Engineering to refine AI prompts, extraction rules, and validation logic.
Essential Functions
- Interpret complex academic datasets and generate insights that support product decision-making and operational efficiency.
- Build and maintain databases, structured data repositories, and data validation systems.
- Acquire, clean, normalize, and verify data from multiple sources, including university catalogs, transcripts, and external databases.
- Detect and resolve data inconsistencies, classification errors, and mapping issues.
- Document workflow improvements and analytics procedures.
- Prioritize data and reporting needs based on business urgency and customer impact.
Minimal Qualifications
- 1+ years of experience as a Data Analyst, Operations Analyst, Academic Evaluator, or similar role.
- Proven experience with data quality assurance, data cleaning, and structured data workflows.
- Working knowledge of SQL and familiarity with data pipelines or ETL principles.
- Strong analytical and problem-solving skills with close attention to detail.
- Experience using Excel and at least one analytical/statistical tool (R, Python, SPSS, SAS, etc.).
- Ability to work in fast-paced environments with strict accuracy and turnaround requirements.
Preferred Qualifications
- Bachelor's degree in Mathematics, Statistics, Computer Science, Information Systems, or related field.
- Experience with academic data, student information systems, or course catalog structures.
- Familiarity with AI-assisted data extraction workflows or Human-in-the-Loop operations.
- Experience with data visualization tools (Looker Studio, Power BI, Tableau).
Top Competencies for Success in This Role
- SQL & Data Querying – Retrieves, joins, and filters data efficiently to support accurate dashboards and audits.
- Data Visualization & Reporting – Builds clear reports that highlight accuracy, workload, and process performance.
- Data Analysis – Identifies trends, patterns, anomalies, and opportunities for workflow improvement.
- Quality Assurance Mindset – Ensures that all outputs meet the 99% accuracy expectation for HITL operations.
- Business & Product Acumen – Understands how data quality impacts TCE customers, PROSPECT functionality, and retention.