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Data Science with less than a year in data analytics and machine learning.
Aspiring Data Science student with a strong foundation in data analytics, statistical analysis, and business intelligence. Skilled in Python, SQL, Excel, Power BI, and Tableau, with hands-on experience in data cleaning, transformation, exploratory data analysis, and dashboard development. Passionate about uncovering meaningful insights from complex datasets and applying data-driven solutions to real-world business challenges. Eager to expand expertise in machine learning, predictive modelling, and artificial intelligence while contributing analytical and problem-solving skills to impactful projects. Committed to continuous learning and leveraging data to support informed decision-making and drive organizational growth.
BLITZ ACADEMY I KOCHI, KERALA
Diploma · Data Science
August 1, 2025 – June 30, 2026
GOSSNER COLLEGE I RANCHI, JHARKHAND
Bachelor of Computer Applications (BCA) · Computer Applications
August 1, 2021 – June 30, 2024
iStudio
Data Analytics Intern
May 1, 2026 – June 1, 2026
India
HOME LOAN DEFAULT PREDICTION
January 1, 2025 – June 1, 2026
Developed a machine learning model to predict loan default risk using historical customer and loan-related data. Performed data cleaning, preprocessing, feature engineering, and exploratory data analysis to identify key risk factors. Implemented classification algorithms and evaluated model performance using accuracy, precision, recall, and F1-score metrics. Visualized customer demographics, financial attributes, and default patterns to generate actionable insights. Applied data-driven techniques to support credit risk assessment and lending decisions. Documented the complete analytics workflow, ensuring reproducibility and model transparency.
View ProjectLOGISTICS OPERATIONS ANALYTICS
January 1, 2025 – June 1, 2026
Analysed logistics and supply chain datasets to evaluate operational efficiency and delivery performance. Performed data transformation, cleaning, and exploratory analysis to identify bottlenecks and optimization opportunities. Developed interactive dashboards and KPI reports to monitor shipment status, delivery timelines, and operational metrics. Utilized data visualization techniques to communicate trends, patterns, and performance insights effectively. Generated actionable recommendations to improve logistics planning and resource utilization. Applied analytical methodologies to support business decision-making and process improvement initiatives.
View ProjectTEXAS SALARY PREDICTION
January 1, 2025 – June 1, 2026
Built a predictive analytics model to estimate salaries based on demographic, educational, and employment-related factors. Conducted extensive data preprocessing, feature selection, and exploratory data analysis to improve model performance. Implemented and compared multiple regression algorithms to identify the most effective prediction model. Evaluated model accuracy using statistical performance metrics and validation techniques. Created visualizations to uncover salary trends and factors influencing compensation levels. Leveraged machine learning techniques to generate insights for workforce and compensation analysis.
View ProjectSALES PERFORMANCE DASHBOARD
January 1, 2025 – June 1, 2026
Designed and developed an interactive sales performance dashboard to monitor revenue, profit, and key business KPIs. Created dynamic visualizations and drill-down reports to analyse sales trends across products, regions, and customer segments. Implemented data modelling and DAX calculations to support advanced business analysis. Automated reporting processes, reducing manual effort and improving reporting efficiency. Enabled stakeholders to make data-driven decisions through real-time performance monitoring and insights. Applied business intelligence best practices to enhance dashboard usability and effectiveness.
View ProjectSTUDENT PERFORMANCE ANALYSIS
January 1, 2025 – June 1, 2026
Conducted comprehensive analysis of student performance data to identify factors affecting academic outcomes. Performed data cleaning, preprocessing, and exploratory data analysis to uncover trends and correlations. Utilized statistical techniques and visualizations to evaluate the impact of demographic and behavioural variables on performance. Developed insightful reports and dashboards to communicate findings effectively. Identified key indicators influencing student achievement and learning outcomes. Applied data analytics methodologies to support evidence-based educational decision-making.
View ProjectMACHINE LEARNING MODELS, MATHEMATICS & STATISTICS (LEVEL 1)
iStudio
June 1, 2026 – Present
PANDAS FOR DATA ANALYSIS CERTIFICATION
iStudio
June 1, 2026 – Present
R PROGRAMMING CERTIFICATION
iStudio
June 1, 2026 – Present
CERTIFICATE OF INTERNSHIP
Data Science (Syntecxhub)
June 1, 2026 – Present
PYTHON PROGRAMMING CERTIFICATION
iStudio
June 1, 2026 – Present
INDUSTRY INTERACTION PROGRAM
Askan Technologies Pvt Ltd
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, covering loan prediction, logistics, salary prediction, sales, and student performance, indicates a broad interest in applying data science across various domains. This adaptability suggests a good cultural fit for dynamic environments. The candidate's stated eagerness to expand expertise in machine learning and AI, coupled with a commitment to continuous learning, aligns with a growth-oriented culture. However, the lack of professional experience beyond a short internship and the ongoing diploma suggest a more junior profile than a typical senior role, which might impact immediate cultural integration into a senior team.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving and analytical thinking, an ability to work in team-based environments, effective communication, and a quick learning aptitude. These soft skills are crucial for a Data Science role, where collaboration, continuous learning, and clear communication of insights are paramount. The project descriptions indicate a structured approach to problem-solving and an understanding of end-to-end analytics workflows.