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Software Engineer with less than a year in Full-stack Development, Generative AI & Data Analytics.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Detail-oriented Data Analyst and Software Engineer with an M.Sc. in Applied Statistics and hands-on experience in machine learning, statistical modelling, Generative AI (RAG systems), and full-stack development. Proficient in Python, R, SQL, Power BI, React, and Next.js. Proven ability to translate complex data into clear, actionable insights and to build scalable, production-ready applications. Seeking to leverage a strong analytical foundation and software engineering experience to drive data-informed decisions in a dynamic organisation.
St. Teresa's College
M.Sc. · Applied Statistics and Data Analytics
August 1, 2023 – June 30, 2025
Sree Sankara College
B.Sc. · Statistics
August 1, 2020 – June 30, 2023
BEM Higher Secondary School
Higher Secondary (Class XII)
June 1, 2018 – May 31, 2020
Infocreon
Software Engineer
April 1, 2026 – Present
India
Infocreon
Generative Al Intern
January 1, 2026 – March 1, 2026
India
Diabetes Prediction Using Machine Learning Models and Feature Engineering
June 24, 2026 – Present
Collected, cleaned, and analysed the diabetes dataset. Trained and evaluated five machine learning models - Random Forest, Decision Tree, XGBoost, Naive Bayes, and Logistic Regression. XGBoost achieved the highest predictive accuracy. Applied feature engineering techniques to improve model performance and interpretability.
Time Series Forecasting Using R
June 24, 2026 – Present
Developed and implemented time series models using R to analyse and forecast trends from real-world datasets. Applied ARIMA and exponential smoothing techniques for forecasting, with results visualised using R graphical libraries to communicate insights effectively to stakeholders.
Cultural Fit Analysis
The candidate's academic background in Applied Statistics and Data Analytics, combined with practical experience in software engineering and Generative AI, indicates a strong interdisciplinary approach. The projects showcase a blend of data science and application development, aligning with roles requiring both analytical rigor and implementation skills. The volunteer experiences suggest a willingness to contribute beyond core responsibilities. However, the experience is relatively short, which might require mentorship in a senior role.
Soft Skills & Operational Fit
The candidate demonstrates analytical thinking, communication, adaptability, and collaboration through project descriptions and roles. Experience in building POCs and contributing to UI/UX improvements suggests a proactive and user-centric approach. Participation in code reviews and CI/CD pipelines indicates an understanding of operational best practices.