Software Engineer • Data & Healthcare Analytics • MS CS (Data Science) @ USC

Roshan Dharan Shashidharan

Los Angeles, CA (USC) • Bengaluru, India

I am a Master’s student in Computer Science (Data Science) at the University of Southern California, with a strong foundation in software engineering, data analytics, and healthcare technology. I currently work as a Software Engineering Intern at the Keck School of Medicine of USC, where I contribute to building and improving healthcare-focused software and data systems that support clinical research and medical initiatives.

Previously at Oracle Health, I delivered custom healthcare data reporting and analytics solutions for large-scale clients, including Children’s National Hospital (Washington, DC). My work leveraged SQL, BI automation, and cloud platforms such as Snowflake, Databricks, AWS, GCP, and OCI, supporting NIH-backed studies, predictive analytics efforts, and enterprise BI migration initiatives.

I have been honored with the Oracle Pinnacle Award, Champion of Service Award, Round of Applause, and multiple Spot Awards, reflecting a proven track record of solving complex problems and driving measurable impact in high-stakes healthcare environments.

MS CS (Data Science) • USCHealthcare Technology & AnalyticsPython • Java • SQLSnowflake • Databricks • AWS • GCP • OCI
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Education

Academic background with a focus on data science, large-scale systems, and applied engineering.

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University of Southern California

Master of Science in Computer Science (Data Science) • Aug 2025 – Present • Los Angeles, CA

Graduate study in data science, large-scale data systems, and applied machine learning with a focus on healthcare technology and cloud-native analytics.

REVA University

Bachelor of Technology in Computer Science and Engineering • Jul 2019 – Jul 2023 • Bengaluru, India

GPA: 3.97/4. Coursework: Data Structures and Algorithms, Object-Oriented Programming (Python/Java/C++), Advanced DBMS, Operating Systems, Machine Learning, Artificial Intelligence, Cloud Computing, Big Data, and Data Science with R.

Highlights

Representative work spanning healthcare analytics, enterprise reporting, and applied machine learning.

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Healthcare Software - Engineering Imapct

Delivered measurable improvements to reporting performance and operational efficiency in enterprise healthcare environments.

  • Led advanced analytics initiatives at Children’s National Hospital across 17+ departments, cutting report runtimes by 30–40%.
  • Designed SQL and ETL pipelines processing 600,000+ patient records/day, shaping $200M+ revenue-impacting decisions.
  • Built compliant 340B, HIDI, and CLABSI audit solutions, reclaiming 114+ hours/year and reducing pharmacy drug spend by over $12M annually.

Others

Built and deployed end-to-end ML workflows for clinical and engineering use cases.

  • Multimodal ICU outcome prediction using LSTM vitals and BioClinicalBERT embeddings with 6–8% AUROC lift over NLP-only baselines.
  • EV battery SoC/SoH prediction over 5,000+ charging cycles using deep learning, with a peer-reviewed journal publication.
  • Deployed models as REST services with CI/CD integration for reproducibility and experimentation.

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Experience

Role-by-role impact with quantified outcomes in enterprise healthcare environments.

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Projects

Filter and search across personal work, healthcare reporting builds, and analytics initiatives.

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