DL.

Data Analyst

Devin Lee

Data analyst with 3+ years across heavy equipment, e-commerce and oil & gas. I build data validation, ETL automation and Power BI dashboards that keep reporting accurate, then use the data to find what the business should fix.

Experience
3+ years in data analytics
Focus
Data quality, SQL, Python, Power BI
Industries
Heavy equipment, retail, e-commerce, oil & gas
Education
B.Eng. Geological Engineering, Trisakti University
Location
Jakarta, Indonesia
Work setup
Remote (APAC preferred, or global) or hybrid in Jakarta
View my experience LinkedIn GitHub
Portrait of Devin Lee

Experience

Operations-heavy roles where the data had to be right before anyone could act on it.

  1. Jul 2026 – Sep 2026

    Data Analyst

    PT. Kawan Lama Group, Jakarta
    • Managed data requests from cross-functional teams: extracting, preparing, validating and delivering data according to business requirements.
    • Monitored and maintained Power BI dashboards to keep sales, customer and operational data accurate, consistent and reliable.
    • Performed data validation and reconciliation by comparing source data with dashboard outputs, identifying discrepancies and coordinating fixes with IT.
    • Worked with IT and stakeholders to investigate and resolve data, dashboard and system issues affecting reporting accuracy.
    • Used Excel, SQL, Python, Power BI and SAP ECC for data extraction, processing, validation and reporting.
    • Initiated and built Python-based ETL automation to process and transform datasets with millions of rows, speeding up repetitive data preparation.
    • Supported testing of an internal AI-powered analytics tool, checking prompt-based outputs against expected sales and product data and reporting inconsistencies to engineering.
    • Troubleshot Google Apps Script and Power Automate workflows used for data requests and automated dashboard issue notifications.
  2. Mar 2024 – Jul 2026

    Senior Data Analyst

    PT. Sany Makmur Perkasa, Jakarta
    • Led exploratory and performance analysis of operational, workforce and cost data to define the KPIs management uses for decision-making.
    • Designed and owned semi-real-time Python automation to monitor resource availability, operational readiness and utilisation for maintenance and resource planning.
    • Developed and maintained executive dashboards in Looker Studio and Power BI for operational performance, resource availability and KPI trends.
    • Established automated data validation and cleaning pipelines across departments, raising reporting accuracy from 60–65% to 85–90%.
    • Supported root cause analysis by analysing historical operational and resource trends to identify the drivers of performance gaps.
    • Aligned data definitions, reporting standards and performance metrics with operations and management teams.
    • Designed and deployed 4 internal web apps (Google Apps Script, HTML, CSS, JavaScript) for data input and automated recording, cutting manual reporting work by more than 50%.
  3. Jan 2024 – Feb 2024

    Data Scientist (project-based)

    ID/x Partners × Rakamin Academy
    • Delivered an end-to-end analytics project covering data preparation, exploratory analysis and insight generation to support business decisions.
    • Applied statistical analysis and predictive techniques to identify the patterns and drivers behind case outcomes.
  4. Oct 2022 – Apr 2023

    Key Account Management, FMCG

    Lazada Indonesia, Jakarta
    • Analysed FMCG seller performance and campaign participation with Excel and SQL-based reporting.
    • Built KPI reports to monitor campaign effectiveness, seller performance and growth trends.
    • Provided data-driven insights to improve campaign performance and support commercial decisions.
  5. Nov 2019 – Feb 2020

    Junior Geologist

    PetroChina International Jabung, Jakarta
    • Performed quantitative analysis on petrophysical and reservoir data (porosity, permeability, water saturation) to support operational and asset decisions.
    • Ensured data quality, validation and consistency of log and mudlog datasets, reducing interpretation errors.
    • Integrated multiple geological and operational data sources for performance evaluation and reservoir modelling.
    • Applied statistical methods to validate reservoir properties and analytical results.
    • Worked with engineers and senior geologists to turn analytical findings into operational and exploration strategies.

Achievements

Measurable results from my work in data.

50%+

less manual reporting work after automating data collection and reports

60→90%

reporting accuracy, lifted from 60–65% to 85–90% with automated validation pipelines

4

internal web apps shipped to standardise how operational data is captured

Millions

of rows handled by Python ETL I built to replace repetitive data preparation

Projects

Five end-to-end analyses, from raw data to recommendation. Every number on this site is produced by code you can read and rerun on GitHub.

Simulated dataSQLPythonProcurementInventory

Heavy equipment spare parts procurement analytics

Two years of spare-parts purchasing (USD 51M, 14 suppliers, 420 parts, 4 sites) for a heavy-equipment contractor. I analysed spend and ABC classes, scored suppliers on OTIF, quality and lead-time reliability, measured the cost of urgent and off-contract buying, ran a 3-way match on invoices, and set safety stock for critical parts.

~$522ksavings identified per year, from contract compliance, invoice checks and fewer urgent orders
Read case study View code
Supplier performance scoreout of 100
Simulated dataPythonData qualityESG

Hotel utility data pipeline and ESG reporting

40 hotels in 8 countries send monthly electricity, water and gas figures by hand. The pipeline standardises them, reconciles every value against the utility bill (including bills on offset cycles), fills gaps, logs every change for audit, and outputs Scope 1 and 2 emissions.

99.5%of injected data errors caught, with zero correct values changed by mistake
Read case study View code
Errors caught by typecaught / injected
Real data, 98k ordersSQLCohortsRFM

E-commerce growth and customer retention

SQL analysis of Olist, a Brazilian marketplace: growth KPIs with window functions, monthly cohort retention, RFM segmentation and category Pareto. It ends with what makes a customer come back.

3.0%of customers ever order twice; a late first delivery cuts that by a further 22% (p = 0.002)
Read case study View code
Monthly GMV, R$Jan 2017 – Aug 2018
Real data, 95k deliveriesPythonLogistic regressionRCA

Delivery experience root cause analysis

Why do customers leave 1–2 star reviews? I split each order into approval, seller handling and carrier transit, controlled for other factors with a logistic regression, and traced where lateness comes from.

13.9×higher odds of a 1–2 star review when an order is late; most of the delay happens in carrier transit
Read case study View code
Share of 1–2 star reviewsby days late
Simulated dataSQLReliabilityRCA

Heavy equipment availability and downtime

A 48-unit fleet across 4 sites over a full year. Using SQL on hour-meters, shift hours and work orders, I separated lost hours into rain standby, breakdowns, waiting for parts and overdue maintenance, then sized the fix for each.

2,170 hof machine time recoverable per year at one site by stocking critical spares
Read case study View code
Hours to restore a breakdown, by siteaverage

Skills

B.Eng. Geological Engineering, Trisakti University, plus Hacktiv8's full-time data science programme.

Analysis and SQL

  • SQL
  • CTEs
  • Window functions
  • Python (pandas)
  • Statistics
  • Advanced Excel

BI and visualisation

  • Power BI
  • DAX
  • Data modelling
  • Looker Studio
  • Dashboard design

Data quality and automation

  • ETL
  • Validation
  • Reconciliation
  • UAT
  • Apps Script
  • Power Automate

Performance analytics

  • KPI design
  • Root cause analysis
  • Cohort and RFM
  • Reliability (MTBF, MTTR)

Tools

  • SAP ECC
  • Git
  • DuckDB
  • Google Workspace

Certifications

  • BCG Data Science (Forage)
  • Python (HackerRank)
  • ID/x Partners PBI
  • DV360 Master Course

Let's discuss how I can help your team

I'm open to data analyst and data operations roles: remote (APAC preferred, or global) or hybrid in Jakarta. Reach me by email or WhatsApp.

Email lee.devinlee14@gmail.com
Phone / WhatsApp +62 812-9629-0390
Chat on WhatsApp LinkedIn GitHub