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Data Science with less than a year in Python, SQL, and Machine Learning
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 Computer Science (Data Science) graduate with hands on experience in Python, SQL, Power BI, and Machine Learning. Skilled in data analysis, dashboard development, forecasting, and business intelligence reporting. Experienced in analyzing large datasets, building predictive models, and developing interactive dashboards to generate actionable business insights. Adept at working across the full data lifecycle, form data cleaning and analysis to visualization and predictive modelling. A quick learner with strong analytical thinking and a collaborative mindset, ready to contribute from day one.
Vidyavardhini's College of Engineering & Technology, Mumbai University
B.E. · Computer Science Engineering (Data Science)
August 1, 2023 – June 30, 2026
Pravin Patil College of Engineering & Technology, Bhayander
Diploma · Computer Engineering
August 1, 2020 – June 30, 2023
Holy Angels English High School, Bhayander
S.S.C.
N/A – May 31, 2020
Fraud Detection in Online Transactions
June 1, 2026 – Present
Analyzed imbalanced transaction datasets to identify fraudulent patterns using anomaly detection techniques. Applied feature engineering and visualization to highlight key fraud indicators for stakeholder reporting. Developed Power BI dashboards to present fraud trends and risk insights.
Bank Loan Analytics Dashboard
June 1, 2026 – Present
Developed an interactive Bank Loan Analytics Dashboard to analyze loan performance and borrower behavior. Used SQL to calculate key KPIs including loan applications, funded amount, amount received, interest rate. Performed Good Loan vs Bad Loan analysis to assess portfolio quality and credit risk. Built Power BI visualizations for monthly trends, state-wise analysis, loan purpose, loan term, and home ownership insights. Utilized Excel for data cleaning, validation, and preprocessing to support reporting and decision-making.
Inventory Demand Forecasting
January 1, 2025 – January 1, 2026
Analyzed 10,000+ historical sales records using Python and Pandas to identify seasonal demand trends and patterns. Developed a hybrid forecasting model combining ARIMA, XGBoost, and LSTM achieving low MAPE. Performed customer behavior analysis to enhance prediction accuracy and optimize inventory planning. Built interactive visualizations using Matplotlib and Seaborn to communicate insights to non-technical stakeholders.
Cultural Fit Analysis
The candidate's projects demonstrate a breadth of interests within data science, including academic, personal, and financial analytics applications. This diversity, coupled with stated interests in machine learning research and business intelligence, suggests a curious and adaptable individual. The collaborative mindset mentioned in the professional summary indicates a potential for good team integration. However, the lack of professional experience means cultural fit is primarily inferred from project work and self-described attributes.
Soft Skills & Operational Fit
The candidate highlights analytical thinking, attention to detail, problem-solving, team collaboration, and time management as key strengths. These are valuable for a Data Science role, indicating a proactive and organized approach to project work. The project descriptions suggest an ability to work across the data lifecycle and communicate insights to non-technical stakeholders.