
Data Science with less than a year in Data Analysis & Machine Learning.
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Detail-oriented Data Science and Data Analyst with strong knowledge of Python, SQL, Excel, Power BI, and Machine Learning using Scikit-learn. Skilled in data cleaning, exploratory data analysis (EDA), data modelling, and dashboard creation to generate meaningful insights. Experienced in writing SQL queries, analysing datasets, and building interactive Power BI dashboards. Passionate about transforming raw data into actionable insights and supporting data-driven decision making. Committed to continuous learning and improving analytical and technical skills.
SRM Arts and Science College
Bachelor of Science · Computer Science
August 1, 2022 – June 30, 2025
Career Solutions
Data Science Intern
November 1, 2025 – Present
India
Power BI – Netflix TV & Shows
December 1, 2025 – June 1, 2026
Analysed Netflix content dataset using MySQL. Wrote SQL queries to explore trends in genres, release years, and ratings. Performed data analysis to understand content distribution and streaming patterns. Built an interactive Power BI dashboard to visualize key insights and trend.
View ProjectOLA Bike ride
December 1, 2025 – June 1, 2026
Performed a machine learning model to predict OLA bike ride requests using historical demand data. Performed data preprocessing and exploratory data analysis (EDA) to understand ride patterns. Implemented the model using Python and Scikit-learn. Analysed peak demand hours and ride request trends.
View ProjectHospital
December 1, 2025 – June 1, 2026
Analysed hospital dataset using SQL and Power BI to extract meaningful insights. Performed data cleaning using Power query and advanced SQL queries to prepare and analyse healthcare data. Implemented data modelling in Power BI to structure and optimize the dataset. Developed an interactive Power BI dashboard to visualize key healthcare metrics. Analysed patient distribution, hospital performance, and satisfaction scores.
View ProjectSQL- Layoff dataset
December 1, 2025 – June 1, 2026
Cleaned and analysed a real-world global layoffs dataset using MySQL. Performed data cleaning and preprocessing to improve data quality. Wrote SQL queries using joins, aggregations, subqueries, and window functions. Analysed layoff trends by company, industry, and year. Generated insights from data to support data-driven decision making.
View ProjectMachine Learning Cancer cell
December 1, 2025 – June 1, 2026
Built a machine learning classification model to predict whether breast cancer tumours are benign or malignant. Performed data preprocessing and feature selection to prepare the dataset for modeling. Trained and evaluated the model using Python and Scikit-learn. Applied machine learning techniques to improve prediction accuracy.
View ProjectRetail Order
December 1, 2025 – June 1, 2026
Performed data cleaning and transformation using Power Query. Built interactive dashboards in Power BI to visualize sales and order insights. Executed SQL queries for business data analysis. Used Python (Pandas, NumPy) for data manipulation and analysis. Generated insights from retail order data to support business decision making.
View ProjectSQL for Data Visualization
Simplilearn
June 1, 2026 – Present
Data Visualisation
Forage
June 1, 2026 – Present
Introduction to Data Analytics
Simplilearn
June 1, 2026 – Present
Introduction to Python
Unknown
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project portfolio demonstrates a diverse range of applications (layoffs, entertainment, healthcare, retail, transportation, medical diagnosis), indicating adaptability and a broad interest in applying data science across different domains. The ongoing internship and certifications suggest a proactive learning attitude, which aligns well with a culture of continuous improvement. The focus on practical, real-world problems in personal projects also indicates a results-oriented mindset. However, the candidate is still early in their career, and their experience is primarily academic and personal projects, which limits the assessment of their fit within a professional team environment.
Soft Skills & Operational Fit
The candidate's resume highlights a 'detail-oriented' approach and a 'commitment to continuous learning,' which are positive indicators for operational fit. The project descriptions suggest an ability to translate raw data into actionable insights, crucial for a data science role. However, without direct assessment data on collaboration or problem-solving under pressure, a comprehensive evaluation of soft skills is limited.