Data Scientist in Cloud

Hard Skills

- Cloud Platforms: AWS (SageMaker, Lambda, S3), Azure AI, Google Cloud (Vertex AI, BigQuery)

- Data Modeling & Machine Learning: Regression, Classification, Deep Learning, NLP, Time Series Analysis

- Data Engineering: ETL pipelines, Apache Airflow, Spark, Kafka

- Programming Languages: Python, R, SQL, Java

- Deployment & CI/CD: Docker, Kubernetes, Jenkins, Terraform

- Tools & Frameworks: TensorFlow, PyTorch, scikit-learn, XGBoost, Hugging Face

Soft Skills

- Analytical Thinking & Problem Solving

- Cross-Functional Communication

- Agile Development & Collaboration

- Strategic Planning & Leadership

- Innovative Thinking & Adaptability

*Senior Data Scientist – Cloud Platforms*

*TechNova Solutions, San Francisco, CA*

August 2022 – Present

- Led the migration of data science workflows to AWS, reducing processing times by 35% through optimized serverless architectures and cost-efficient resource management.

- Developed robust NLP models for customer feedback analysis, improving sentiment detection accuracy by 12%, which informed targeted marketing strategies.

- Automated data pipeline orchestration using Apache Airflow, enabling scheduled retraining of ML models with minimal downtime.

- Collaborated with DevOps to containerize ML services with Docker and deploy on Kubernetes, ensuring seamless scaling during high demand periods.

*Data Scientist – Cloud Data Innovation*

*CloudIQ Analytics, New York, NY*

June 2018 – July 2022

- Designed and implemented predictive models on Google Cloud, increasing fraud detection rates by 22% for client financial services.

- Built a real-time anomaly detection system using Kafka and Spark Streaming, reducing false positives by 18%.

- Worked closely with product teams to incorporate ML models into client-facing dashboards, enhancing user engagement and data transparency.

- Conducted workshops on cloud AI services, boosting team proficiency in cloud-native model deployment and management.

*Data Analyst & Cloud Support Engineer*

*CloudBridge Inc., Boston, MA*

September 2015 – May 2018

- Supported cloud infrastructure deployment for data projects, providing analytics insights and system troubleshooting.

- Developed dashboards using Power BI and Tableau, presenting key KPI trends and forecasts to C-suite executives.

- Assisted in transitioning legacy on-prem data warehouse systems to cloud environments, ensuring data integrity and security.

**Master of Science in Data Science**

Stanford University, Stanford, CA — 2013-2015

**Bachelor of Science in Computer Science**

University of California, Berkeley, CA — 2009-2013

- AWS Certified Machine Learning – Specialty (2023)

- Google Cloud Professional Data Engineer (2024)

- Azure Data Scientist Associate (2022)

- Certified Kubernetes Administrator (CKA) (2021)

Cloud-Optimized Recommendation Engine

- Deployed a scalable recommendation system using AWS SageMaker, enabling personalized content for over 10 million users. Reduced latency by 40% with serverless inference.

Automated Data Governance Framework

- Developed an automated data auditing and compliance pipeline on Azure, leveraging Azure Data Factory and Data Lake, improving data quality checks and reducing manual errors.

Real-Time Customer Churn Prediction Model

- Implemented on GCP using BigQuery ML and Pub/Sub for streaming, achieving a churn prediction accuracy of 85% which directly increased retention strategies.

- Cloud: AWS, Azure, GCP

- ML Frameworks: TensorFlow, PyTorch, scikit-learn

- Data Orchestration: Apache Airflow, Kafka

- CI/CD & Containers: Docker, Kubernetes, Terraform, Jenkins

- Data Visualization: Tableau, Power BI

- Databases: PostgreSQL, BigQuery, DynamoDB

- English (Native)

- Spanish (Fluent)