Open to opportunities

Daniel Retta

@danielretta

Senior Data Scientist building production ML systems and large-scale data pipelines that drive measurable business impact.

United States

Message

What I'm looking for

I’m looking for a role where I can engineer production ML and large-scale data pipelines—strengthening reliability, observability, and real-time inference—while partnering cross-functionally to deliver measurable business outcomes.

I’m a Senior Data Scientist with a strong engineering background, focused on building production-grade ML systems and large-scale data pipelines. I design end-to-end machine learning workflows—advanced analytics, real-time inference systems, and scalable data architectures—aimed at measurable business impact.

At Microsoft, I designed and deployed data pipelines for Azure Databricks workloads, improving throughput by ~35%, reducing pipeline failures by ~28%, and cutting incident detection time by ~30%. At Google and Intel, I built exabyte-scale processing pipelines and monitoring/analytics backends, improving processing efficiency by ~25% and detection accuracy by ~20%, while also automating reporting and improving operational efficiency by ~30%. I bring an engineering mindset to reliability, observability, and collaboration—partnering across teams, mentoring engineers, and standardizing documentation so systems and models can scale confidently.

Experience

Work history, roles, and key accomplishments

Current

Software Engineer / Data Scientist

Current

Microsoft

Mar 2024 - Present (2 years 4 months)

Designed and deployed data pipelines for Azure Databricks workloads, improving data processing throughput by ~35% and enabling scalable analytics. Implemented data validation and anomaly detection, improved pipeline reliability (down ~28% failures), and built monitoring dashboards to reduce incident detection time by ~30%.

Azure Databricks Data Pipelines ETL ELT Data Validation Anomaly Detection Monitoring Observability Distributed Systems Logging Data Modeling Dashboarding Python SQL Machine Learning predictive modeling Feature Engineering Statistical Modeling

Software Engineer / Data Scientist

Google

Jul 2019 - Mar 2023 (3 years 8 months)

Built large-scale data processing pipelines for analyzing security data across exabyte-scale infrastructure, improving processing efficiency by ~25%. Developed anomaly detection and statistical models (accuracy up ~20%), performed exploratory data analysis and feature engineering, and mentored engineers while conducting 100+ interviews.

Data Pipelines Data Processing Anomaly Detection Statistical Modeling Feature Engineering Data Quality Data Validation Machine Learning predictive modeling Distributed Systems Technical Documentation Mentorship Python SQL

Software Engineer / Data Analyst

Intel Corporation

Jul 2015 - Jul 2019 (4 years)

Developed data collection and processing pipelines for SSD validation systems and built analytics tools and dashboards to monitor test results, improving operational efficiency by ~30%. Automated reporting using Python (turnaround time up ~25%) and used statistical analysis to identify performance bottlenecks.

Data Pipelines Data Collection Dashboarding Monitoring Python Statistical Analysis predictive modeling Machine Learning Data Validation SQL Data Quality Performance Bottlenecks Automation Cross Functional Collaboration

Software Engineer Intern

Intel Corporation

Jun 2013 - Sep 2013 (3 months)

Developed automation scripts and data validation tools to improve workflow efficiency and implemented secure data validation techniques for enterprise systems. Debugged and improved application features.

Data Validation Debugging Python ETL ELT