- →Built an AI agent that auto-generates SQL to accelerate ad-hoc data exploration, and integrated AI across the daily analytics workflow.
- →Designed and ran A/B tests with hypothesis testing & statistical significance analysis to drive product decisions.
- →Automated weekly & monthly reporting pipelines in R, Python and Excel for global stakeholders.
- →Tracked acquisition, retention, churn and cohort/funnel performance across Brazil, Japan & Vietnam; defined core KPIs (LTV, ARPU, ROAS).
Aslıhan
Akar
Turning six years of data into decisions, now teaching it to think with AI.
I'm an analytical, results-driven data professional with six years across data modeling, reporting, statistical analysis, and dynamic dashboards.
Expert in SQL, Python and R, with growing depth in AI-driven analytics workflows. I don't just measure products. I build them: my solo iOS apps, Lucid and ListingLedger, are live on the App Store. Off the clock, I read psychology to sharpen how I read people and data alike.
- →Automated issue follow-up files with Power Query, significantly cutting manual reporting time.
- →Used SAS & Excel for audit analytics to identify regulatory risks and led regional issue closures.
- →Created financial control scenarios and perpetual monitoring reports using advanced SQL.
- →Transformed complex financial data into meaningful executive-level reports.
ListingLedger
A B2B expense-tracking platform for US real estate agents, live on the App Store. Expenses are tracked per property listing, with automatic bank sync, GPS mileage capture at the IRS rate, receipt OCR, and Schedule C ready tax reports. Built solo end-to-end: SwiftUI + SwiftData client on a Python serverless backend.
View on the App Store →Lucid · Dream Insights
A solo iOS app designed, built and shipped end-to-end to the App Store with AI-assisted development. LLM-powered analysis surfaces recurring themes, emotional signals and reflection prompts from journal entries, with in-app subscriptions, push notifications and privacy-first local storage.
Stock Price Prediction
Master's thesis project predicting stock prices with deep learning. Built and trained LSTM neural networks on financial time-series, engineered technical indicators as features, and evaluated forecast accuracy across different market conditions.