Siri Shetty.K

Computer Science Engineering graduate and IEEE-published researcher with hands-on experience through 3 data science internships. Skilled in machine learning, predictive analytics, data visualisation, and dashboard development using Python, SQL, Power BI, and Flask. Built and deployed ML models for real-world applications including energy forecasting and deep learning-based image classification with 97% accuracy.

Passionate about solving business problems using data-driven insights and seeking opportunities as a Data Analyst, Junior Data Scientist, or Junior ML Engineer.

Data Science & AI Intern - Palle Technologies - Bangalore

(2026-01 - 2026-05)

• Analysed structured datasets of 10,000+ records using Python (Pandas, NumPy) and SQL to uncover patterns, identify anomalies, and support data-driven decision-making.
• Engineered end-to-end data preprocessing pipelines covering missing value imputation, outlier detection, and feature normalisation, improving downstream model input quality.
• Designed and deployed interactive Power BI dashboards to communicate KPIs and analytical findings to cross-functional teams in a clear, business-friendly format.
• Automated repetitive data transformation workflows using Python scripts, reducing manual processing effort and improving pipeline consistency.

Artificial Intelligence and Cloud Computing Intern - SuprMentr

(2026-02 - 2026-05)

• Built and evaluated supervised ML classification models using Python and scikit-learn, applying data preprocessing techniques including encoding, scaling, and train-test splitting.
• Performed exploratory data analysis (EDA) and feature selection on structured datasets to identify key predictors and improve model accuracy.
• Collaborated with remote mentors to scope, prototype, and deliver machine learning mini-projects on schedule, demonstrating strong analytical thinking and time management.
• Worked with structured datasets to perform statistical analysis and support predictive modelling tasks using supervised learning techniques

Data Science Intern - Teach Maven

(2025-09 - 2025-11)

• Conducted exploratory data analysis (EDA) on real-world datasets using Pandas and Matplotlib, identifying patterns and anomalies that shaped preprocessing and modelling strategies.
• Assisted in data preprocessing workflows - cleaning raw data, encoding categorical variables, and handling missing values - to improve pipeline consistency and reduce manual effort.
• Documented analytical findings and generated visualisations that supported clear communication of insights to team leads.
• Contributed to improving workflow efficiency by organizing datasets, documenting preprocessing steps, and validating cleaned data before model training.

B.E. - Computer Science and Engineering - Adichunchanagiri Institute of Technology, Chikmagaluru (2022 - 2026)