Focus : Data Analyst, ESG Research Analyst, Policy Analyst
Specifications : Economics, Econometrics, Statistics, Operations Research, Data Visualization, Machine Learning
Skills
Technical Skills Programming Languages: Python, R-Programming, MySQL Econometric Tools: EViews, Stata Software: MS Word, MS Excel, MS PowerPoint, Canva, Power BI, Programming Languages: Python, R-Programming, MySQL Econometric Tools: EViews, Stata Software: MS Word, MS Excel, MS PowerPoint, Canva, Power BI, I possess a thorough understanding of various statistical methods: Descriptive Statistics: Proficient in summarizing and describing the essential features of datasets. Inferential Statistics: Experienced in using Z-tests, t-tests, and Chi-square tests to infer characteristics of populations from sample data. Probability Distribution Theories: Familiar with different probability distributions to model and analyze random variables. Sampling Techniques: Skilled in designing and implementing various sampling techniques to ensure representative data for analysis., In terms of economics, I possess comprehensive knowledge of cross-sectional, panel, and time series data. I utilize econometric methods like linear regression, Pooled OLS, and traditional OLS to estimate economic models and uncover relationships between variables. My ability to forecast economic trends and employ Vector Autoregression (VAR) models enables me to predict interdependencies between different economic factors. Furthermore, I apply the Augmented Dickey-Fuller test to assess the stationarity of time series data, ensuring accurate forecasting and model performance., I bring a strong set of soft skills to any project or team. My sincerity and dedication have been recognized through academic achievements and awards. I am highly adaptable, thriving in new environments and quickly learning new tasks. My collaborative nature and strong communication skills make me an effective team player, while my problem-solving abilities ensure that I can tackle complex challenges and provide actionable insights. Altogether, I aim to combine my technical proficiency, economic expertise, and soft skills to contribute meaningfully to organizations and drive impactful results.,Languages
English, Hindi, Bangla,Hobbies
Acquiring information about climate change, Singing, Dancing, Watching Movies/Series.
Summary
I am an aspiring economist and analytics enthusiast with expertise in Python, R, MySQL, and econometric tools like EViews and Stata. My skills encompass data analysis, statistical modeling, and economic forecasting, supported by a strong foundation in descriptive and inferential statistics. I excel in creating impactful visualizations and effective communication, aiming to drive meaningful insights and results in data-driven decision-making and environmental research.
Employment History
DMR Intern , National Coalition For Natural Farming
Led a comprehensive farm data analysis project, leveraging farm diary records from over 200 farmers to extract valuable insights that directly informed decision-making. Employed advanced Excel techniques to enhance data accuracy, ensuring the highest quality results for strategic planning. Played a pivotal role in advancing the development of a proof of concept for natural farming by 60%, utilizing Excel tools to drive data-driven outcomes. My responsibilities encompassed data compilation, meticulous cleaning, statistical analysis, and troubleshooting, which significantly contributed to sustainable agricultural practices. This experience underscores my expertise in data analytics, environmental impact assessment, and policy evaluation.
Education History
Internships
Led farm data analysis, using farm diary records of over 200 farmers, and employing advanced Excel for accuracy. Played a key role in furthering the development of a proof of concept by 60% for natural farming using Excel tools. Responsibilities included data compilation, cleaning, statistical analysis and troubleshooting.
Collaborated with Madhya Pradesh Pollution Control Board (MPPCB) to evaluate industrial emissions and recommend sustainable practices. Optimized data quality through rigorous validation and cleansing procedures using python and performed correlation analysis to detail out key areas to focus on . Streamlined documentation by reorganizing 500+ files, spreadsheets, and reports; created polished project presentations that boosted senior staff efficiency by 40% and improved stakeholder communication by 30%.
Projects
Developed a management system using MySql and Python-Jupyter for efficient assignment data handling, improving data security and accessibility.
Utilized Z-tests, t-tests, and Chi-square tests to reveal significant differences in environmental concern based on education and gender, providing valuable insights for targeted sustainability initiatives and policy evaluations using Excel and Python.
I developed several modules that contributed to a comprehensive understanding and analysis of industrial pollution and environmental monitoring in Madhya Pradesh. Below is an overview of the modules developed:
1. Industrial Monitoring Systems Analysis
Tasks Performed:
- Analyzing data from continuous monitoring systems to assess real-time pollution levels.
- Utilizing statistical tools to identify trends and anomalies in pollution data.
Content:
- Continuous Monitoring Systems Analysis.ipynb: This module focused on analyzing data from continuous emission monitoring systems (CEMS) installed in various industries. The analysis included processing large datasets to extract meaningful insights on pollution trends, identifying anomalies, and assessing compliance with regulatory standards. The use of Python for statistical analysis and visualization helped in presenting the data in a clear and concise manner.
2. Madhya Pradesh Industrial Landscape Analysis
Tasks Performed:
- Understanding the industrial scenario in Madhya Pradesh, including key industries and their environmental impact.
- Evaluating the effectiveness of pollution control measures adopted by these industries.
Content:
- Madhya Pradesh Industrial Landscape.ipynb: This module provided a detailed analysis of the industrial landscape in Madhya Pradesh. It included an assessment of the major industries contributing to pollution, their production capacities, and the types of pollutants they emit. The analysis also covered the effectiveness of existing pollution control measures and recommendations for improvements.
3. Correlation Analysis of Industrial Pollutants
Tasks Performed:
- Conducting correlation analysis to understand the relationship between different pollutants and industrial activities.
- Identifying key factors influencing pollution levels in various industries.
Content:
- 10 Industries_Correlation Analysis.ipynb: This module focused on conducting correlation analysis to identify the relationships between different pollutants emitted by major industries. By analyzing the data, I was able to identify key factors influencing pollution levels and provide insights into how industrial activities impact environmental quality.
4. Data Analysis for Selected Industries
Tasks Performed:
- Performing detailed data analysis for selected industries to assess their environmental impact.
- Using statistical techniques to evaluate the effectiveness of pollution mitigation measures.
Content:
- Selected Industries_Data Analysis_Main.ipynb: This module involved detailed data analysis for selected industries, focusing on their environmental impact and the effectiveness of pollution mitigation measures. The analysis included statistical techniques such as regression analysis and hypothesis testing to evaluate the performance of these measures and provide actionable recommendations.
5. Data Cleaning and Consolidation
Tasks Performed:
- Cleaning and consolidating datasets to ensure data quality and accuracy for analysis.
- Preparing datasets for further statistical analysis and visualization.
Content:
- clean.csv and CONSOLIDATED DATA.csv: These datasets were cleaned and consolidated to ensure data quality and accuracy. The process involved handling missing data, removing outliers, and standardizing data formats. The cleaned datasets served as the foundation for subsequent analysis and visualization tasks.
6. Environmental Surveillance and Reporting
Tasks Performed:
- Compiling and analyzing data for environmental surveillance and reporting.
- Preparing fact sheets and presentations to communicate findings effectively.
Content:
- Environment Surveillance Centre_Madhya Pradesh Industrial Landscape.csv: This dataset was compiled to provide a comprehensive overview of the environmental surveillance activities in Madhya Pradesh. The analysis included assessing the effectiveness of monitoring systems and preparing fact sheets and presentations to communicate findings to stakeholders.
- Industrial Monitoring Systems.csv: This dataset was used to analyze the performance of industrial monitoring systems in Madhya Pradesh. The analysis focused on identifying gaps in monitoring coverage and recommending improvements to enhance environmental surveillance.
7. Industry Details Compilation
Tasks Performed:
- Compiling detailed information on various industries, including their environmental impact and mitigation measures.
- Preparing comprehensive reports to support decision-making and policy formulation.
Content:
- Industry Details.csv: This dataset included detailed information on various industries, such as their production capacities, types of pollutants emitted, and pollution control measures adopted. The compilation of this information supported the development of comprehensive reports and informed decision-making and policy formulation.
Applied Python for data visualization and machine learning, enabling the creation of insightful visualizations and predictive models/forecasting (Linear Regression and VAR model) for effective waste management strategies using World Bank’s “What a Waste 2.0” data.