Data Scientist | GenAI | Data Analyst | Python | SQL

I am a Data Scientist with 3+ years of experience designing predictive models and scalable data systems across CPG, credit risk, and healthcare. My work focuses on turning large, complex datasets into robust analytical solutions that support operational and strategic decision-making.

I work across the end-to-end data science lifecycle, including exploratory analysis, feature engineering, model development, validation, and deployment in production environments. I use SQL and Python to build reliable data pipelines, feature stores, and machine learning workflows.

• Demand forecasting and predictive modeling
• Credit scoring and risk analytics
• Data pipelines and analytical systems
• Machine learning workflows for production environments
• Legacy analytics pipeline modernization
• Model interpretability, data traceability, and reproducibility
• Generative AI applications for analytics and automation

• Languages: Python, SQL, JavaScript
• Data Science: Pandas, NumPy, Scikit-learn, statistical modeling
• Databases: SQLite, relational databases, analytical SQL
• Backend & APIs: Flask, FastAPI, REST APIs
• Web & Mobile: HTML, CSS, React Native, Expo
• Tools: Git, GitHub, data pipelines, automation workflows
• AI: Generative AI, LLM-based analytics, prompt engineering

• Sistema de Vendas Nani
  Sales and management system focused on real operational workflows.

• Commercial Control Tools
  Applications and utilities for business monitoring, sales control, and process automation.

• Analytics & Automation Experiments
  Projects exploring backend systems, data automation, APIs, and applied AI workflows.

I am currently exploring how Generative AI can support analytics workflows, automate repetitive analytical tasks, and accelerate model development while keeping results interpretable, traceable, and reproducible.

• GitHub: @rauenh
• LinkedIn: Hingryd Rauen