Albar Pambagio Arioseto's Resume
Albar Pambagio Arioseto
Data analyst building end-to-end analytics pipelines across FMCG, retail, and healthcare. Open to relocate.
PDF Version ↗About
Work Experience
Education
Universitas Terbuka
Pacmann
Bangkit Academy (Google, Tokopedia, Gojek, Traveloka)
Skills
Languages
- Python
- SQL
- TypeScript
Data Stack
- PostgreSQL
- DuckDB
- dbt
- pandas
- ETL Pipeline Design
- Star Schema Modeling
Analysis & Forecasting
- Exploratory Data Analysis
- Time-Series Analysis
- Forecasting (AutoARIMA, AutoETS)
- Funnel Analysis
- LTV Analysis
Visualization
- Power BI
- Recharts
- Marimo
Infrastructure & Tools
- Next.js
- TypeScript
- Cloudflare Pages
- GitHub Actions
- AI-Assisted Development
Projects
Indonesia Food Price IntelligenceMay 25, 2026
Built a procurement intelligence tool for FMCG Category Managers sourcing rice, cooking oil, sugar, and flour across Indonesia. Analyzed 17 years of WFP price data across 224 markets to map seasonal spikes (Ramadan premium on sugar, Q2 harvest discount on rice), a 30% persistent price gap between Eastern Indonesia and Java for cooking oil, and a 3-month leading relationship between oil and flour prices. Includes a 6-month price forecast with explicit confidence intervals to guide procurement timing decisions.
- Python
- DuckDB
- dbt
- AutoARIMA
- AutoETS
- Next.js
- Cloudflare Pages
Pharmacy Retail Sales AnalyticsMay 18, 2026 — May 26, 2026
Analyzed a hospital pharmacy's full-year sales data to surface margin risk and inform 2016 procurement decisions. Identified 2 branded SKUs selling below cost and mapped revenue concentration patterns across inpatient and outpatient channels. Delivered a 3-page interactive dashboard — with a margin threshold slider and CSV export — for the Pharmacy Director and Finance team to act on product pricing and procurement priorities.
- Python
- PostgreSQL
- Next.js
- Recharts
- shadcn/ui
- GitHub Actions
- Cloudflare Pages
Olist Marketing Funnel: Channel Performance & LTV AnalysisMay 8, 2026 — May 18, 2026
Investigated why Social — Olist's second-highest-volume acquisition channel — converted at only half the rate of Paid and Organic Search. Found the root cause in channel deal composition: Social's closed deals skewed nearly twice as heavy in high-maintenance seller profiles compared to other channels, a structural drag on conversion rather than a lead quality issue. Delivered a 4-page Power BI dashboard with channel LTV and funnel analysis to support VP Marketing budget allocation for Q3 2018.
- Python
- PostgreSQL
- Power BI