CV
Data Analyst
Technical Skills: Python, SQL, R, PowerBI, Excel, Latex, GitHub
Education
- Ph.D., Statistics North Dakota State University (Aug 2024)
M.S., Applied Mathematics University of Dhaka (December 2015) B.S., Mathematics University of Dhaka (August 2014)
Work Experience
Researcher @ North Dakota State University (Statistics Department) (August 2021 - August 2024)
- Proposed an empirical likelihood test for detecting community structure in both weighted and unweighted networks, addressing limitations in conventional hypothesis testing approaches focused primarily on unweighted networks.
- Utilized R programming for advanced statistical analysis, including the computation of test statistics, empirical likelihood ratio distributions, and p-values, while evaluating type I error rates and the power of the empirical likelihood test against traditional statistical frameworks by conducting 500 simulations.
- Extended simulations to weighted networks using Beta and Gamma distributions for edge weights, analyzing test accuracy and power for different probabilities.
Graduate Teaching Assistant @ North Dakota State University (August 2021 - August 2024)
- 3 years of experience in conducting 10+ laboratory sessions per semester for classes of 25+ students using JMP software for courses such as Introduction to Statistics and Regression Analysis, providing hands-on training in statistical methodologies.
- Assessed and evaluated student performance through grading and offering constructive feedback, enhancing their statistical understanding and problem-solving skills.
- Facilitated tutoring sessions focused on improving students’ grasp of data analysis and statistical concepts, fostering academic development.
Deputy Director of Pricing & Analytics Team @ Chaldal Limited (October 2018 - July 2021)
- Led a 10-member team responsible for pricing over 4,000 products, optimizing strategies to increase profitability while reducing the product pricing update cycle from 72 hours to 24 hours.
- Established a 5-member analytics team, leveraging SQL and Excel to generate data-driven insights, enabling strategic decisions on consumer behavior and market trends.
- 2.5+ years of experience in defining and tracking key performance metrics across multiple business units, focusing on clear visualizations using BI tools to enhance decision-making for senior management.
- Designed and implemented a fraud detection system to identify and mitigate risks within 24 hours, saving costs and improving operational efficiency by enabling rapid financial audits and risk assessments.
- Conducted SQL and Excel training for 30+ team members, empowering cross-functional teams to independently generate reports and data solutions, thereby increasing data accessibility and driving business innovation.
- Reconciled and analyzed disparate data sources to detect inconsistencies, enabling accurate financial modeling, risk forecasting, and the identification of critical business risks.
- Created specifications for over 20 reports and dashboards, aligning with business needs and available data elements, enhancing decision-making accuracy for senior management.
Data Analyst & Growth Hacker @ Rokomari.com (April 2016 - August 2018)
- Structured and optimized CRM analytics to enhance data collection and analysis, supporting strategic decision-making in both pre- and post-branding performance evaluation.
- Utilized product analytics to track and interpret user activity across web and app platforms, driving the optimization of digital experiences based on behavioral insights.
- Collaborated with cross-functional teams to develop Key Performance Indicator (KPI) dashboards, ensuring the clear visualization of metrics for senior leadership and supporting data-driven decision-making.
- Curated and executed growth hacking strategies through the design and analysis of A/B tests for 30+ experiments, leveraging statistical analysis to evaluate and optimize experiments.
- 2+ years of experience in generating financial reports and providing actionable insights for monthly and quarterly business reviews, contributing to business growth and operational efficiency.
Projects
Testing Community Structure With Empirical Likelihood
Designed and evaluated a novel empirical likelihood test for detecting community structure in network data, demonstrating superior statistical power through extensive simulations compared to existing methods. This absence of a community within the network has inspired us to explore and address this issue and motivate us to test the existence of community structure through our thesis research.
Exploring E-Commerce Reviews on Amazon using Bidirectional Recurrent Neural Network (RNN) and Long-Short Term Memory (LSTM) For Sentiment and Recommendation Analysis
This project aimed to explore the relationship between various variables in Amazon product reviews, employing univariate and multivariate analyses alongside a bidirectional recurrent neural network (RNN) with long-short-term memory (LSTM) units for recommendation and sentiment classification.
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Presentations
Testing Community Structure With Empirical Likelihood - Red River Valley Statistical Conference, Spring 2023 & Spring 2024