Kevin Bai

Kevin Bai

Python | SQL | Machine Learning | Data Warehouse | Data Visualization

Skills & Expertise

Programming
& Analysis

Python
Pandas, NumPy, scikit-learn, TensorFlow, PySpark workflows
PostgreSQL
Schema design, indexing, query optimization, analytics modeling
R
Statistical analysis, hypothesis testing, predictive modeling
Jupyter
Notebook-based analysis, experimentation, model prototyping
NumPy
Vectorized computation, numerical methods, performant transforms
Pandas
Data wrangling, feature engineering, time-series preparation

Data Engineering
& Platform

Apache Airflow
DAG orchestration, dependency management, scheduled workflows
Apache Spark
Distributed compute, large-scale transforms, ETL acceleration
Databricks
Lakehouse workflows, notebook collaboration, production jobs
Docker
Containerized services, reproducible environments, local parity
dbt
Modular SQL transforms, testing, documentation, lineage tracking
GitHub Actions
CI/CD pipelines, automated checks, deployment workflows

Cloud
& Warehousing

AWS
Redshift, Glue, Lambda, S3 data platform architecture
Azure
Analytics services, storage integration, enterprise deployment
Google Cloud
Managed analytics services and scalable cloud-native workloads
Snowflake
Warehouse modeling, secure sharing, performance tuning
BigQuery
Serverless analytics, partitioned tables, high-volume SQL
Data Warehousing
Dimensional modeling, governance standards, data quality controls

ML
& Visualization

scikit-learn
Feature pipelines, model validation, classical ML productionization
TensorFlow
Neural networks, deep learning experiments, model iteration
PyTorch
Model prototyping, experimentation, GPU-enabled training
Power BI
DAX modeling, semantic layers, executive-ready reporting
Looker
LookML modeling, governed explores, self-serve analytics
Microsoft Excel
Advanced formulas, pivots, scenario analysis, stakeholder delivery

Domain Expertise

  • Product Analytics

    Connect product performance and experiments to better business decisions.

  • Revenue Optimization

    Identify growth opportunities and evaluate the drivers of margin efficiency.

  • Fraud Detection

    Surface suspicious patterns and streamline investigation workflows.

  • Customer Retention

    Use predictive insights to understand churn risk and support retention.

  • KPI Development

    Translate business goals into consistent metrics and actionable dashboards.

  • Data Governance

    Build trust in data through shared definitions, documentation, and quality controls.

  • Cross-functional Leadership

    Align technical and business teams to deliver shared data initiatives.

  • Stakeholder Communication

    Turn complex analysis into clear recommendations and decision-ready reporting.