Portfolio

Viet Tran – Senior Data Analyst

Turning complex data into business clarity 7+ years of experience in analytics, automation, and visualization

About Me

I’m Viet Tran, a Senior Data Analyst with over 7 years of experience turning complex data into clear business stories. I specialize in data warehouse design, SQL modeling, and dashboard storytelling that empower teams to make informed decisions.

I thrive at the intersection of data, operations, and business strategy, helping organizations transform manual workflows into automated, scalable systems.

Highlight Projects

Auto Reconcile Dashboard – OnPoint E-commerce (2024)

Context: Manual reconciliation between Finance and Operations took 7 working days each cycle.
Approach: Designed a config-driven framework using PostgreSQL + Python + Power BI for automated matching and audit-ready reports.
Impact: Reduced reconciliation time from 240 working hour/year; improved accuracy, transparency, and monthly closing efficiency.

SKU Performance & Inventory Dashboard – OnPoint E-commerce (2024)

Context: Excess stock and poor visibility slowed inventory turnover.
Approach: Built an interactive Power BI dashboard integrating sales, inventory, and product data; applied A/B/C classification & aging logic.
Impact: Identified 15% slow-moving stock; improved rotation; aligned Finance, SC, and Commercial decisions.

Campaign & Business Readiness – OnPoint (2024)

Context: Needed real-time monitoring for 9.9 / 11.11 / 12.12 peak events.
Approach: Developed Power BI dashboards and SQL pipelines to track conversion, fulfillment, and logistics readiness in real-time.
Impact: Enabled instant insights, faster response times, and improved cross-team coordination.

Operation & Customer Insight Reporting – Bizzi Vietnam (2022–2024)

Context: SaaS fintech startup required unified visibility of customer behavior and product performance.
Approach: Built Operation & Customer Journey dashboards via SQL + Looker Studio; conducted churn & retention analysis with Python.
Impact: Increased retention; enabled data-driven decisions; saved hours of manual reporting weekly.

Market Pricing & Forecast – A Dong ADG Corporation (2020–2022)

Context: No structured pricing or forecasting model for plastic distribution.
Approach: Created SQL pipelines + Excel models; implemented a data governance framework across departments.
Impact: Supported pricing strategy; improved accuracy of demand forecasting; built unified business metrics.

Technical Stack

• Database & Query: PostgreSQL, MySQL, NoSQL
• Programming: Python (pandas, polars, selenium, scikit-learn, pyspark)
• Visualization: Power BI, Looker Studio, Excel
• Data Engineering: BigQuery, API integration, ETL automation
• Workflow & Automation: Airflow, Python scripting, Data migration

Work Philosophy

I believe great analytics start with understanding the business. Data should serve decisions — not just dashboards.

• Clarity: Make complex data understandable
• Scalability: Build systems that grow with business
• Trust: Ensure every metric can be explained

Beyond Data

Outside of dashboards, I enjoy teaching analytics and writing on Rabit Learn Data where I share stories connecting business sense and data sense. I mentor young analysts and help teams transform insights into action.

Let’s Connect

LinkedIn | Gmail