Open to opportunities

Stephen Raj S

@stephenrajs

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Data Science and Machine Learning intern focused on building accurate models and clean data-driven insights.

India

Message

What I'm looking for

I’m looking for an entry-level role in data science or machine learning where I can deploy models, build data pipelines, and improve outcomes through clean data, feature engineering, and careful experimentation.

I’m a data science professional-in-training with an M. Sc. in Data Science and hands-on experience deploying machine learning models. As a Machine Learning Intern, I improved prediction accuracy by 15% through hyperparameter tuning and ensured 99% data quality by cleaning 10,000+ records for model training.

I also built data pipelines and performed feature engineering for business solutions as a Data Science Intern. I used SQL to extract and analyze relational data and reduced query time by 30%, then conducted exploratory data analysis to surface trends and support stakeholder recommendations.

My projects reflect how I like to work: turning data into reliable decisions and user-ready tools. I’ve developed a Python CNN (TensorFlow) for leaf disease detection deployed via Streamlit, built symptom-based disease predictors, and performed large-scale analytics and NLP sentiment classification—backed by training through my data analytics and Python certifications.

Experience

Work history, roles, and key accomplishments

Machine Learning Intern

Nitroware Technologies

Jan 2024 - Mar 2024 (2 months)

Deployed classification ML models and improved prediction accuracy by 15% through hyperparameter tuning. Cleaned and validated 10,000+ records to achieve 99% data quality for model training, and presented findings that informed business decisions.

Machine Learning Classification Hyperparameter Tuning data preprocessing Data Validation Python Team Collaboration

Data Science Intern

GR Soft Technology Pvt. Ltd.

May 2023 - Jun 2023 (1 month)

Designed data pipelines and performed feature engineering on 5,000+ records to uncover actionable insights. Used SQL to extract and analyze relational data, reducing query time by 30%, and conducted exploratory data analysis to support stakeholder recommendations.

Data Pipelines SQL Relational Databases Data Extraction Data Analysis