Usmanjon Abduraimov

Data Scientist & Analytics Engineer · Python · ML · Django · BI

  • Long-Term Resident of Japan (定住者 Teijūsha) — no visa sponsorship needed
  • Kaggle Notebooks Expert — peak global rank #1,919

Data scientist and analytics engineer who builds the whole system, not just the script: from Oracle and PostgreSQL extraction through validation, analytics and machine learning to dashboards and secure Django web applications — then deploys and documents it. 5+ years across banking, tax administration and accounting consulting in Uzbekistan and South Korea, and a KAIST Techno-MBA on a Korean Government Scholarship (GMAT 710). Most of my systems were owned and delivered solo, end to end. Looking for a data, analytics or Python backend role in Japan, inside a strong engineering team.

Professional experience

Risk Analytics & Data Platform Engineer

02/2025 – Present

Kapitalbank JSCB · Tashkent

  • Designed and built, as the sole engineer, a secure internal Django analytics platform used by management and the risk department.
  • Built the end-to-end pipeline: Oracle → preprocessing → validation → aggregation → analytics → dashboards → reports.
  • Automated 100% of daily and monthly regulatory and management reports, freeing two analysts from routine manual work.
  • Delivered portfolio analytics, NPL tracking, trend and growth modelling and KPI monitoring, behind role-based access.
  • Wrote the full technical and data-processing documentation. The system runs only on the bank’s internal network; a demo on synthetic data is available on request.

Python · Django · Pandas · Polars · SQL · Oracle · PostgreSQL · Plotly

Data & Cost Analytics Engineer

10/2024 – 02/2025

Dasan DMC · Seoul

  • Built a cost-modelling and profitability analytics system for automotive parts.
  • Automated data collection, transformation and scenario analysis.
  • Owned the data logic, models and analysis end to end.

Python · Pandas · SQL

Analytics Automation Engineer (Contract)

02/2024 – 10/2024

Shinhan Accounting Corporation · Seoul

  • Built a Django analytics system end to end: data ingestion, validation, processing, analytics and reporting.
  • Cut manual analysis and reporting time by more than 50%.
  • Built Tableau dashboards for client scoring, portfolio quality and risk indicators.
  • Owned the architecture, backend and data logic.

Python · Django · Pandas · SQL · Tableau

Risk Analyst

2020 – 2021

State Tax Committee of Uzbekistan · Tashkent

  • Led the digitalisation of the waybill system, from paper to online.
  • Designed the data workflow logic and validation structure.
  • Cut processing time by ~50% and made the process transparent.

Credit Analytics Analyst

2019 – 2020

Alokabank · Tashkent

  • Prepared analytical summaries and risk indicators for 200+ loan cases.
  • Developed a structured evaluation logic for credit decisions.

Key projects

Powerty — data-driven learning platform

2026 – Present

Founder & engineer · powerty.uz

  • Designed and built a bilingual (English/Uzbek) platform for GMAT, SAT, IELTS, TOPIK, Japanese and school maths: 1,300+ lessons, 20,000+ auto-graded questions, 800+ graded readings and timed mock exams.
  • Engineered an adaptive digital-SAT simulator (module routing, raw → 400–1600 scaled scoring) and a GMAT Focus simulator on one shared exam engine.
  • Built content pipelines guarded by automated “answer gates” — scripts that recompute every answer key by an independent route (brute force over fractions, state-space search) before import.
  • Runs in production on PostgreSQL + Railway: a cron-driven Telegram bot, an installable PWA, full i18n, TTS audio and headless-Chrome PDF generation.

Python · Django · PostgreSQL · AWS S3 · Git/GitHub · Railway · Bootstrap · AI-assisted development (Claude Code)

Kaggle — Notebooks Expert

14 public notebooks · 5 medals · 490 forks · kaggle.com/usmanjon

  • House-price regression (20,640 districts): treated multicollinearity with engineered ratio features, stratified split, one-hot + scaling pipeline; tuned a random forest with 5-fold grid search — R² 0.60 (linear) → 0.72 on held-out test.
  • Home-advantage hypothesis test (380 Premier League matches): one-tailed two-sample t-test derived by hand and checked against SciPy — t = 2.22, p = 0.013.
  • Indonesian schools (215,372 rows): joined census data scraped from Wikipedia, caught impossible coordinates and filtered ~3,000 to valid bounds before mapping.
  • South Korea demographics 2000–2022 (17 regions, monthly): time-series resampling showed deaths overtaking births nationwide in 2020.

scikit-learn · SciPy · Pandas · Plotly · Seaborn · Matplotlib