Internship: Data Analytics and Reporting – Lea

What You’ll Do

1. Build Insightful Dashboards
Design and develop reporting dashboards to track claims KPIs, operational performance, and AI decision support metrics.

2. Own the Reporting Pipeline
Independently extract, transform, and visualize data from MySQL databases, CSVs, APIs, and internal systems.

3. Turn Business Requirements into Insights
Collaborate with stakeholders to understand reporting needs and translate them into technical solutions.

4. Experiment with Modern Tools
Evaluate and propose innovative tools and techniques (e.g. dbt, modern BI tools, scripting for automation, AI/ML-based analytics) that improve reporting processes and output.

5. Ensure Data Quality
Validate data integrity and implement checks to ensure the reliability of reports used by our operations and leadership teams.

6. Analyze Performance
Monitor and report on AI model decision accuracy, content generation reliability, and resolution turnaround times.

Requirements:

1. Independence & Ownership
You are a self-starter who can work with minimal technical guidance and proactively solve data problems.

2. Curiosity & Innovation
You actively seek out new analytics tools, learn them quickly, and assess their relevance for our use cases.

3. SQL Proficiency
Confident in querying and manipulating complex datasets in MySQL or similar environments.

4. Data Visualization Skills
Experienced in BI tools like Power BI, Tableau, AWS QuickSight, or others.

5. Excel Expertise
Comfortable using Excel/Google Sheets for advanced analysis (pivot tables, VLOOKUP, filters, etc.)

6. Strong Analytical Thinking
Able to uncover patterns, trends, and outliers, and translate them into insights that support decision-making.

7. Communication Skills
Capable of explaining insights to a non-technical audience clearly and professionally.

Nice to Have

1. Experience with Programming Languages (Python, R) for advanced analytics and data manipulation
2. Understanding of Data Warehousing and ETL processes
3. Familiarity with AI/ML Analytics approaches for evaluating model performance and data quality
4. Experience with Cloud Analytics Platforms (AWS QuickSight, Power BI)
5. Experience with Real-time Analytics and streaming data processing