Maral Amiri

With over 5 years of experience leveraging predictive analytics and machine learning, I specialize in optimizing marketing and sales strategies through data-driven insights. Proficient in Python, SQL, Hive, and Spark, I design robust data pipelines and dynamic dashboards that empower media measurement, profitability analysis, and accurate demand forecasting. I thrive on transforming complex datasets into actionable strategies, collaborating seamlessly with cross-functional teams to drive business performance and growth. Passionate about using data to solve real-world problems and help organizations make smarter decisions.

Data Scientist Intern
Corteva Agriscience – Remote | Jan 2025 – Present

Developed Python/Spark feature-engineering pipeline for real-time data analysis.

Automated large-scale processes, optimizing system resources and improving performance by 15%.

Integrated automated tests into CI/CD pipeline using Jenkins to streamline testing of data workflows.

Data Scientist
San José State University – San José, CA | Jan 2024 – Jan 2025

Led data instrumentation and automated ingestion for 200+ campus facilities, improving data freshness from 24 hours to 2 hours.

Designed predictive models (LSTM, Prophet) for utility cost forecasting, reducing errors by 8% and supporting a $1.2M energy budget allocation.

Collaborated with privacy and legal teams to ensure compliance with data privacy regulations.

Data Analyst
San José State University – San José, CA | Jul 2023 – Dec 2023

Wrote Bash utilities and SQL scripts to merge 10GB of daily building sensor data, implementing QA checks and boosting dataset reliability score from 0.76 to 0.93.

Developed Tableau dashboards to track energy consumption trends, leading to a $300K retrofit initiative.

Senior Program Manager
Mindist International – Tehran, IR | Mar 2017 – Mar 2021

Managed end-to-end media analytics systems, including media-mix tagging and A/B testing for Samsung and Henkel campaigns.

Led cross-functional teams in Spark/Hive cohort analyses, improving customer segment targeting and increasing blended ROAS by 5%.

Automated data processing workflows, reducing manual intervention and improving efficiency for large-scale media campaigns.

Master of Science in Data Science

San Jose State University, San Jose, CA