Hire the Best Quantitative Analysts
in Bangladesh

Good research does not start with a statistical test. It starts with the right question, sound methodology, and analysis that leads to credible findings. With 7+ years of experience, I have supported 100+ research projects across PhD and Master’s research, academic studies, and business analysis, combining research design, academic writing, statistical analysis, data interpretation, and reporting to turn complex research problems into clear, evidence-based results. My work is backed by 100% Job Success, Top Rated status, $60K+ in verified Upwork earnings, an MBA in Marketing, and an ACCA qualification. 🔬 𝗦𝗧𝗔𝗧𝗜𝗦𝗧𝗜𝗖𝗔𝗟 & 𝗗𝗔𝗧𝗔 𝗔𝗡𝗔𝗟𝗬𝗦𝗜𝗦 📊 Data & Exploratory Analysis Data Cleaning | Transformation | Coding | EDA | Descriptive Statistics | Missing Data | Outlier Detection 🧪 Statistical Analysis t-tests | ANOVA | ANCOVA | MANOVA | Chi-square | Correlation | Non-parametric Tests | Effect Sizes | Power Analysis 📈 Regression & Modeling Linear & Multiple Regression | Logistic & Multinomial Regression | Hierarchical Regression | Model Diagnostics 🧠 Advanced Methods Mediation | Moderation | PLS-SEM | SEM | Path Analysis | Bootstrapping 📋 Measurement & Survey Analysis EFA | CFA | Reliability | Validity | Cronbach’s Alpha | Scale Development | Survey Analysis 🛡️ Assumptions & Diagnostics Normality | Linearity | Homoscedasticity | Multicollinearity | Independence | Model Fit | Residual Analysis 📑 Results & Reporting Statistical Tables | Data Visualization | Interpretation | Effect Sizes | Research Findings | Evidence-Based Insights 📚 Academic & Research Dissertations & Theses | Research Design | Methodology | Literature Reviews | Research Papers | Manuscripts | Hypotheses | Conceptual Frameworks 🎯 Research Domains Business & Management | Marketing | Finance & Accounting | HRM | Psychology | Education | Healthcare | Economics | Public Health | Social Sciences 💻 Tools & Software IBM SPSS | R | Python | Stata | SmartPLS | AMOS | Excel 📩 𝗟𝗘𝗧'𝗦 𝗧𝗔𝗟𝗞 Have a research question, dataset, thesis, or statistical challenge? Send me the details. Let’s turn your research into clear, credible results you can confidently present and defend.

My work sits at the intersection of finance, quantitative analysis, and applied AI. In my current role as a Lead AI for Finance Specialist and Solutions Engineer at a finance-focused AI company, I work on applying AI to real finance workflows, with a focus on agent-based systems, workflow automation, financial analysis, reporting, and data processes. I also contribute to educational content that helps finance professionals understand how these technologies can be applied in practical finance settings. My experience has given me a strong foundation across both finance and technology. Before moving into AI for finance, I spent three years working as a quantitative analyst across an asset manager and a fintech. During that time, I worked on NAV reporting for six mutual funds, improved the data correctness of a valuation dashboard by 70 percent through automated validation, and developed an unattended regulatory data pipeline on AWS that ran daily across five asset classes. These experiences shaped how I approach AI and automation today: the technology needs to work within the realities of financial data, controls, validation, and business processes. In my current work, I have developed experience designing AI-assisted workflows and agent-based systems, including systems with multiple specialized roles, validation stages, structured outputs, and automated review processes. I have also worked extensively with Claude, MCP integrations, scheduled workflows, Python, and other tools for connecting AI capabilities with practical finance processes. My focus is not simply on generating outputs with AI, but on understanding how a workflow should operate, where errors can occur, and how validation and controls can be incorporated into the process. I also have experience building financial reporting and analytics solutions, including Power BI dashboards using proper data models, self-updating HTML dashboards connected to structured data sources, and Excel and Apps Script automation for recurring reporting processes. Alongside this, I have built Python-based data pipelines involving web scraping, ETL, MongoDB, InfluxDB, MySQL, and AWS, with particular attention to reliability, idempotency, and unattended operation. My earlier quantitative work also included building and testing systematic research and trading systems. I have worked on backtesting engines built to written specifications, strategy validation using methods such as deflated Sharpe ratios, walk-forward analysis, and permutation testing, as well as live trading systems involving state reconciliation and Docker-based deployment. This background continues to influence the way I approach AI systems, particularly around validation, reproducibility, and distinguishing between a promising demonstration and evidence that a system works reliably. I hold CFA Level I, an MBA in Finance from IBA, University of Dhaka, and an engineering degree from BUET. Across my work, I try to be explicit about the difference between demonstrated capability and proven production performance. Where something has only been tested on demonstration data or validated through backtesting, I state that clearly rather than presenting it as production evidence.

I help researchers, organizations and graduate students turn raw survey and study data into clear, defensible statistical results — and where needed, into publication-ready reports, not just output tables. With 17+ years of experience — including as a team leader on large-scale research and development projects — I specialize in: ✔ Thesis/PhD data analysis — statistical analysis, interpretation, and APA-style reporting for graduate research ✔ Survey data analysis — market research, consumer surveys, and trend analysis, from small to large datasets ✔ Statistical & specialized methods — SPSS, R, Python; hypothesis testing, regression, ANOVA, MCDA/TOPSIS, DIF/GMH, uncertainty quantification ✔ Report writing — turning analysis into clear, well-structured, publication-ready reports My background also includes large-scale field research in Health, Nutrition, Child protection, Environment, Education, and WASH programs — leading household survey data collection (including Kobo Toolbox) for populations as large as 10 million and managing research databases in Access and SQL. This gives me strong practical grounding in real-world data quality, survey design, and messy or complex datasets — skills I bring into every project. ⭐ What I Can Do for You ✔ Clean, validate, and analyze survey/research datasets — small or large, few or many variables ✔ Perform statistical analysis in SPSS, R, or Python, from basic tests to advanced/specialized methods ✔ Support PhD/Masters thesis data analysis with clear, defensible, APA-style output ✔ Write publication-ready reports, not just raw statistical output ✔ Handle large or messy datasets with confidence ✔ Deliver results both researchers and non-technical readers can understand ⚙️ Tools: SPSS | R | Python | Excel | SQL | MS Access | KoboToolbox | PySpark I maintain a 100% Job Success score and Top-Rated status on Upwork. I take pride in accurate, well-documented work — from a single survey analysis to a full thesis-to-publication project.

I am an accomplished Senior Quantitative Analyst with a rich background in developing advanced trading systems, optimizing algorithmic strategies, and spearheading innovation in the financial technology sector. My experience spans leading financial firms, top-tier software companies, and cutting-edge research institutions. I excel at solving complex problems, enhancing trading performance, and driving efficiency through data-driven insights. With a strong blend of technical expertise and strategic thinking, I consistently deliver measurable results, making significant contributions to portfolio management, risk analysis, and software development initiatives.