live reporting tabs
Automated from a pricing workbook through a Python ETL workflow at Avomind.
Data Analyst | Jakarta, Indonesia
I turn messy data into reliable reporting, analytical workflows, and decision-ready insights.
I work across data operations, ETL, reporting, data quality, and applied analytics. My focus is turning inconsistent inputs and repetitive manual work into structured workflows, clear reporting, and analysis people can act on.
Data Analyst is my core role, with supporting depth in automation, forecasting, machine learning, quantitative research, and product delivery.
Explore by hiring need
Start with the evidence closest to the role
Jump to reviewed role evidence or filter case studies by hiring focus.
Professional results
Results from professional work
A few concrete examples from data operations, reporting, and quality work.
candidates in recurring reporting
Supported through two KPI views alongside reporting for 38 to 39 researchers.
data cells cross-checked
Validated after standardizing a 134-column schema across three annual workbooks.
Portfolio
Selected analytical work
Three projects that show how I structure data problems, validate methods, and turn analysis into usable products.
Risk analyticsHistorical evidence live
Ruang Risiko IDX
Indonesian equity risk research that makes returns, volatility, drawdown, downside estimates, direction probabilities, provenance, and model evidence inspectable.
StackNext.js · Vercel · yfinance · GARCH family models
- Built
- A production research interface for five IDX equities plus IHSG, backed by validated market artifacts and archived out-of-sample model evidence.
- Strongest result
- 9,072 successful archived walk-forward forecast rows with 0 failed archived rows.
Risk analytics2026-09-07
Ruang Risiko IDX
36archived model combinations
9,072walk-forward rows
0failed archived rows
Market intelligenceResearch prototype
Cakrawala Intelligence Terminal
Forex-first market and macro research that makes source health, evidence freshness, model state, and decision boundaries visible.
StackPython · Streamlit · market data adapters · model governance
- Built
- A public research terminal across 12 analytical areas, with guarded data ingestion and explicit separation between public research and owner-only analysis.
- Strongest result
- Recorded product scope covers 12 analytical areas with daily research and weekly model-governance design.
Market intelligence2026-08-29
Cakrawala Intelligence Terminal
12public analytical areas
Dailyresearch cadence
Weeklymodel governance
Applied machine learningRebuild tested
SpamShield ML
Cost-aware SMS spam classification where probability quality, threshold policy, artifact integrity, and deployment are evaluated as separate decisions.
StackPython · scikit-learn · FastAPI · Docker
- Built
- A reproducible UCI training path with TF-IDF, model comparison, threshold analysis, integrity-checked artifacts, FastAPI, Docker, and Streamlit delivery boundaries.
- Strongest result
- Validation F1 0.9291 with average precision 0.9788 on the fixed stratified rebuild holdout.
Applied machine learning2026-08-29
SpamShield ML
0.9291validation F1
0.9788average precision
0.0347Brier score
Experience
See full CV Professional experience
Current work across data operations, reporting, automation, and quality review.
Junior Data Controller
Data operations, ETL automation, KPI reporting, dashboard delivery, and quality control for CRM and pricing workflows.
CV evidenceMaintain a 19-field CRM structure, extracting, cleaning, and standardizing lead and client records from varied raw sources in batches of roughly 40 to 60 entries per extraction pass.
More role evidence
- Built and maintain a Python ETL workflow using the Google Sheets API and a service account to automate data flow from the Client Pricing workbook into four live reporting tabs.
- Manage two recurring KPI reporting views supporting structured reporting across 300+ candidates and 38 to 39 researchers.
- Designed and built a six-page Looker Studio dashboard and refined calculations and usability through nine rounds of stakeholder revisions.
- Standardized a 134-column schema across three annual workbooks covering 2024 to 2026, validating 3,500+ data cells through a five-layer cross-check.
AI Data Specialist and QA Contractor
AI response evaluation, training-data design, structured QA, and multilingual review across business, academic, and technical domains.
CV evidenceEvaluate AI-generated response pairs across a seven-dimension quality framework on a one to five scale, with preference rankings and written rationale.
More role evidence
- Researched, built, and quality-checked 15+ original training decks across 14 personal finance subtopics.
- Authored 110 persona-grounded prompts and multi-turn conversation examples for AI training, and reviewed Indonesian AI-generated audio transcripts across four QA cycles.
Independent Financial Market Analyst
Structured USD/JPY market analysis using price behavior, technical indicators, and macroeconomic context.
CV evidenceAnalyzed USD/JPY using technical indicators, historical price behavior, and macroeconomic context across Asian and London trading sessions.
More role evidence
- Used a structured historical review process to compare market conditions, trade decisions, and execution quality over time.
Research and Development Associate
Data-informed internal consulting work using structured analytical frameworks and evidence-based reporting.
CV evidenceContributed to data-driven consulting deliverables for internal organizational projects using structured analytical frameworks and evidence-based reporting methods.
How I work
A practical path from question to evidence
How I structure analytical work, with links to supporting projects and professional experience.
Frame the decision
Start with the decision, reporting need, or quality question before choosing the tool or model.
Validate the inputs
Make data quality, provenance, chronology, and assumptions visible before promoting an analytical result.
Automate repeatable work
Turn recurring manual steps into reproducible workflows when automation improves reliability and reviewability.
Make evidence inspectable
Separate results, validation, limitations, and source status so another person can challenge the conclusion quickly.
Capabilities
Capabilities with evidence
Tools and methods grouped by the work they support, linked to where they appear in practice.
Data analysis and reporting
Python · pandas · NumPy · SQL · R · statistical analysis · KPI reporting
Where I used this
BI and automation
Looker Studio · Google Sheets API · Google Apps Script · ETL scripting · HubSpot CRM · Power BI · Tableau
Where I used this
Applied modeling
scikit-learn · LightGBM · Prophet · GARCH · forecast evaluation · baseline comparison
Where I used this
Delivery and QA
Streamlit · FastAPI · Docker · GitHub Actions · data quality · LLM evaluation
Where I used this
Contact
Let's make data easier to trust and use.
I am interested in Data Analyst work where reporting, automation, data quality, and analytical thinking come together.