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Data Analyst with 2+ years in Python, SQL & Power BI
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Detail-oriented Data Analyst with a strong foundation in Chemical Engineering and hands-on experience in Python, SQL, Power BI, and Excel. Expertise in ETL pipeline development, exploratory data analysis (EDA), and dashboard creation for business intelligence. Skilled in applying statistical techniques, forecasting models, and data-driven approaches to solve real-world industrial and business problems. Proven ability to transform raw data into actionable insights to improve operational efficiency, reduce costs, and enhance decision-making.
SCRIET, CCS University
B.Tech · Chemical Engineering
August 1, 2020 – June 30, 2024
Govt Polytechnic
Diploma · Chemical Engineering
N/A – June 30, 2020
Kisan Inter College, Bhanpur Basti (UP)
High School
N/A – May 31, 2016
Ducat IT Training School
Data Science Intern
August 1, 2025 – Present
India
Star Paper Mills Ltd
Graduate Engineer Trainee
July 1, 2024 – August 1, 2025
India
Chemical Industry Demand & Supply Analysis
June 23, 2026 – Present
• Performed end-to-end analysis on production and demand datasets (10k+ records) • Built ETL pipelines for data preprocessing including handling missing values and outliers • Conducted EDA to identify demand-supply gaps and revenue trends • Developed Power BI dashboards with KPIs such as Demand Forecast and Capacity Utilization • Created DAX measures including Forecast Accuracy and Demand Gap %
Student Data Analysis & SQL Query Optimization
June 23, 2026 – Present
• Designed and analyzed a structured student dataset with fields: ID, Name, Marks, Age, and Branch • Applied SQL queries including SELECT, WHERE, GROUP BY, ORDER BY, and HAVING for data filtering and analysis • Used aggregate functions (COUNT, AVG, MAX, MIN) to derive academic performance insights • Optimized queries using subqueries and conditional filtering for efficient data retrieval • Generated insights on student performance distribution and branch-wise comparison
Smartphone Data Analysis
June 23, 2026 – Present
• Tools: Microsoft Excel (Pivot Tables, Advanced Formulas, Charts) • Implemented data cleaning techniques and designed visualizations (bar charts, line graphs) to display KPIs like total sales, regional performance, and monthly trends. • Analyzed pricing trends and product segmentation using EDA and visualization
Bank Loan Prediction Model
June 23, 2026 – Present
• Tools: Python, Pandas, Scikit-learn, Logistic Regression, EDA • Built Logistic Regression model with ~80% accuracy • Performed feature engineering and model evaluation • Developed a classification model to predict loan approval status based on applicant data (income, credit history, loan amount, etc.). • Performed extensive data preprocessing, including handling missing values, encoding categorical variables, and feature scaling to prepare data for modeling. • Implemented and evaluated a Logistic Regression model, achieving an accuracy of 80% demonstrating the ability to apply machine learning for financial decision-making.
Treated Water Analysis (B. Tech) Research Project
June 23, 2026 – Present
• Conducted experimental research on EC and EO methods for wastewater treatment. • Managed and interpreted experimental data to compare the effectiveness of different treatment methods, demonstrating strong analytical and data interpretation skills
Data Analyst 101
Simplilearn
June 1, 2026 – Present
Power BI
Simplilearn
June 1, 2026 – Present
Introduction to Artificial Intelligence
Simplilearn
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic background in Chemical Engineering, combined with a transition into data analysis, shows adaptability and a willingness to learn new domains. The variety of academic projects (chemical industry, student data, banking, smartphone data) indicates a broad interest in applying data analysis across different sectors. The internship at Ducat IT Training School, while an internship, aligns well with the target role. The certifications further demonstrate a proactive approach to skill development. However, the lack of professional experience beyond an internship and a Graduate Engineer Trainee role (which is not directly data-focused) means there's limited evidence of cultural fit within a dedicated data team environment.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work with diverse datasets and apply analytical methods to solve business problems. The 'Graduate Engineer Trainee' role suggests experience in process analysis and collaboration, which are valuable for operational fit. However, the descriptions lack specific examples of problem-solving approaches, teamwork dynamics, or communication of insights to non-technical stakeholders, which are crucial for senior roles.