[Your Full Name]
[Your Phone Number] | [Your Email] | [City, State]
LinkedIn: [Your LinkedIn URL] | GitHub: [Your GitHub URL]

PROFESSIONAL SUMMARY
Full-stack Data Scientist with [X] years building data infrastructure and ML products from scratch. Thrives in fast-paced startup environments wearing multiple hats. Proven ability to deliver end-to-end solutions from data collection to production deployment with limited resources.

TECHNICAL SKILLS
Full Stack ML: Model development, deployment, monitoring, data pipelines, analytics
Programming: Python, SQL, JavaScript, Bash
ML/DL: Scikit-learn, TensorFlow, PyTorch, XGBoost
Data Engineering: Airflow, Spark, Kafka, ETL pipelines
Cloud & DevOps: AWS, GCP, Docker, Kubernetes, CI/CD, Terraform
Web: Flask, FastAPI, React (basic), REST APIs
Databases: PostgreSQL, MongoDB, Redis, Elasticsearch

PROFESSIONAL EXPERIENCE

Data Scientist / Founding Data Scientist
[Startup Name], [City, State]
[Start Date] – Present
• First data hire building entire data infrastructure and ML capabilities from ground up
• Developed [number] ML products generating $[amount]M in revenue and serving [X]K users
• Built data pipeline processing [amount] of data daily using Airflow and Spark
• Deployed [number] models to production with monitoring and automated retraining
• Created analytics dashboards informing product strategy and go-to-market decisions
• Collaborated directly with founders on data strategy and product roadmap
• Wore multiple hats: data scientist, data engineer, ML engineer, analyst

Data Scientist
[Previous Startup/Company], [City, State]
[Start Date] – [End Date]
• Joined as employee #[X] contributing to [key company milestones]
• Built MVP of [product/feature] in [timeframe] leading to $[amount] funding round
• Implemented experimentation framework enabling data-driven product decisions
• Developed customer segmentation and targeting models for growth team
• Created internal tools and dashboards used by [X] teams

PRODUCT & IMPACT

[Product Name]
• Built end-to-end ML-powered [product description]
• Solo owned from concept to production deployment in [timeframe]
• Technologies: [Full stack: data collection, model, API, frontend]
• Impact: [Users, revenue, or key metrics]

Data Infrastructure
• Built scalable data pipeline from scratch handling [volume]
• Implemented data warehouse, ETL processes, and analytics stack
• Reduced data processing time from [X] hours to [Y] minutes
• Enabled self-service analytics for [number] non-technical team members

Growth Analytics
• Developed attribution model tracking customer journey across [X] touchpoints
• Built cohort analysis framework measuring retention and LTV
• Created experimentation platform running [Y] tests per month
• Insights drove [Z%] improvement in key growth metrics

ENTREPRENEURIAL PROJECTS

[Side Project or Personal Venture]
• Built and launched [description] serving [X] users
• Technologies: [Stack used]
• Outcome: [Traction, learning, or pivot]

EDUCATION
[Degree Name], [Field]
[University Name], [City, State]
Graduation: [Year]

STARTUP SKILLS
• Rapid Prototyping: Ship MVPs quickly and iterate based on feedback
• Resourcefulness: Deliver maximum impact with limited resources
• Cross-functional: Work effectively with product, engineering, sales, marketing
• Ambiguity: Thrive in unclear situations and define own priorities
• Scrappiness: Build, measure, learn mentality