Poojitha Guduru
Data Automation Intern @Springer Capital
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WORK HISTORY
Data Automation Intern @Springer Capital
US
Supporting the automation of data collection and reporting processes to enhance operational efficiency across investment and analytics teams.Collaborating with cross-functional teams to identify manual workflows and design automated solutions using Python and scheduling tools.Assisting in building data pipelines and preprocessing datasets to ensure accuracy and consistency for analytics purposes.Gaining hands-on experience with Power BI for creating interactive dashboards and SQL for querying and transforming financial datasets.Learning best practices in data governance, process documentation, and version control in a fast-paced financial environment.
EDUCATION
New England College
Master of Science - MS
ABOUT POOJITHA GUDURU
My name is Poojitha Guduru, I am doing a Masters degree in Data Science and Analytics with a Computer Science and Engineering background, I’m passionate about leveraging data to solve complex, real-world problems. My journey includes hands-on experience in machine learning, data architecture, and software engineering. I developed a liver disease prediction model as part of a published research project, showcasing my commitment to impactful, health-focused analytics. Throughout my studies, I’ve engaged in hackathons and internships, including at Accenture and Tata, where I applied skills in Python, SQL (PostgreSQL, MySQL, MySQL Server), and algorithm design to real-world data challenges. I’ve also tackled IoT and sensor-based projects, which taught me about data collection and transformation for impactful analysis. With expertise in Python, SQL, and data architecture, I am exploring opportunities in data science, analytics, and data engineering roles where innovation meets meaningful work. I’m particularly interested in roles that support diversity, education, or social good, blending technical skills with societal impact. Let’s connect if you’re interested in collaborating on data-driven projects, sharing insights, or exploring data science’s potential to create positive change.
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