Calvin Wang

Data and software engineer with experience building analytics platforms and risk infrastructure in both enterprise and high-frequency trading environments. Proficient in Python and SQL, with hands-on experience designing data pipelines, event-driven automation systems, and real-time financial data ingestion. Proven track record of transforming complex datasets into scalable services and actionable insights across trading, risk, and business teams.

Risk Portfolio Developer at Kronos Research (2023-02 – Present)

• Spearheaded the refactoring of legacy Python codebases into modular, high-availability services, implementing FastAPI to replace manual database workflows with scalable internal API endpoints.
• Engineered and optimized end-to-end analytics pipelines using Airflow, achieving a 25% reduction in latency for firm-wide PnL and Cost-of-Capital reconciliation.
• Designed and deployed event-driven automation engines for margin rebalancing and real-time LTV threshold monitoring, eliminating manual intervention during high-volatility market events.
• Developed robust ingestion layers to interface with global exchange APIs, processing high-velocity funding and margin data streams into MySQL for real-time risk analysis.
• Developed and maintained an enterprise-wide auto-hedging system and real-time exposure monitor; engineered logic to automatically neutralize market exposure, ensuring firm-wide risk stayed within strict regulatory and internal limits.
• Acted as a primary technical bridge between trading, risk, and operations teams to deliver data-driven solutions and improve enterprise risk mitigation workflows.

Data Analyst at L'Oréal Taiwan (2021-06 – 2023-02)

• Designed and maintained a scalable data lake and warehouse on GCP, utilizing Airflow and dbt to orchestrate complex transformations and ensure 100% data dependency accuracy.
• Developed and productionized machine learning models (Python, Sklearn) that successfully doubled online conversion rates (CVR).
• Executed A/B testing frameworks and product recommendation logic, driving a 17% growth in Average Unit Sale.
• Leveraged SQL and Python to perform advanced customer segmentations, increasing event attendance by 38% while reducing operational costs by 14%.

Bachelor of Business Administration in Finance | Business Data Analysis Program – National Taiwan University