Akash Srinivasan
Data Scientist @DigitalOptometrics
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WORK HISTORY
Data Scientist @DigitalOptometrics
US
This position directly relates to my Master of Science in Data Science degree. The role involves designing and developing data-driven solutions, building Power BI dashboards, developing ETL pipelines, and performing advanced data modeling and statistical analysis. My graduate coursework in data analytics, machine learning, statistical modeling, database systems, and predictive analytics prepared me to analyze large operational datasets, develop SQL-based transformations, implement AI-driven automation solutions, and generate actionable business insights. The position requires applying data science methodologies such as data cleansing, validation, forecasting, predictive modeling, and performance optimization, which are core competencies developed through my academic training and research projects. This role utilizes technical skills in SQL, data modeling, machine learning, and business intelligence that directly align with my degree program.
EDUCATION
University of Arizona
Master's degree
Meenakshi Sundararajan Engineering College
Bachelor of Engineering - BE, Computer Science
ABOUT AKASH SRINIVASAN
At the intersection of data, intelligence, and automation — As an AI & Data - Automation Engineer I build AI systems that grow smarter with every interaction.At Digital Optometrics, I design and deploy RAG chatbots, vectorized search pipelines, and LLM-integrated dashboards that replace manual reporting with real-time insights. With hands-on expertise in Azure AI Search, OpenAI embeddings, Pinecone, and LangChain, I build systems that connect structured and unstructured data turning complexity into clarity. Previously, during my Data Engineering work with Operations Team, I lead the Intern Development team on optimizing ETL pipelines, automated KPI tracking, and enhanced Power BI reporting efficiency for doctor service and operational teams, improving accuracy and refresh performance.Earlier, at Banner University Medical Center, I built patient-outcome dashboards and Python-driven validation workflows that strengthened data integrity across clinical reporting pipelines. These experiences reinforced my ability to merge AI innovation with practical healthcare impact.I am currently completing my M.S. in Data Science at the University of Arizona (graduating December 2025), specializing in scalable LLM deployment, cloud automation, and vectorized data retrieval systems. I’m actively exploring full-time opportunities where I can apply my skills in AI engineering, data automation, and intelligent system design to drive innovation and real-world impact.Beginning early 2026, I will be available for full-time opportunities focused on building intelligent data ecosystems that evolve continuously — delivering insights that are faster, smarter, and more human-centered.
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