UX
AI
DATA
I am a dedicated and forward-thinking professional with a strong academic background and diverse experience in the field of technology and data science. With a Bachelor of Science degree in Business Information Technology and a Master's degree in Applied Statistics and Data Science, I bring a unique blend of business acumen, analytical skills, and a passion for solving complex problems.
User Interviews
Usability Testing
Persona Development
Wireframing and Prototyping
Information Architecture
Task Analysis
Data Cleaning and Preprocessing
Statistical Analysis
Machine Learning
Data Visualization
Python and R Programming
SQL and Database Management
Survey Design
Qualitative Analysis
Quantitative Analysis
Requirement Analysis
Market Analysis
Dashboard Design
Frontend Development
Report Writing
Web Research
Agile Methodology
Linux OS
Levereging AI Tools
University of Barishal
2025 – PresentJahangirnagar University
2021 – 2023University of Greenwich
2015 – 2020Lead Analyst & Program Manager
Full-Time
2024 - Present
Perceive Now Inc.
UX Consultant
Freelance
2023 - Present
Upwork
Database Specialist
Part-Time
2016 - 2020
Nexgen Electronics LTD
Learned essential project management principles, including project lifecycles, stakeholder communication, task prioritization, and risk management. Gained practical tools for planning, organizing, and delivering successful projects.
Learned to build modern data warehouse solutions on Azure, covering data ingestion, processing options, and enterprise analytics with Synapse, Databricks, and HDInsight.
Gained expertise in relational and non-relational data concepts, SQL databases, and NoSQL systems. Learned to choose appropriate workloads and integrate Azure SQL securely for enterprise use.
Introduced data fundamentals including ETL, data modeling, SQL queries, and cloud-based engineering.
Specialized in Oracle database administration, backup & recovery, and performance tuning.
Practical training in user research, wireframing, prototyping, and usability testing for digital products.
Topics Covered: Data Scraping Data Preprocessing Data Cleaning Deep Learning Computer Vision Machine Learning
The Indian subcontinent is blessed with a diverse range of mammal species, each contributing to the region's rich biodiversity. However, wildlife conservation faces significant challenges, including the need for efficient species identification, behavior understanding, and habitat preservation. Our project addresses these challenges by harnessing AI technology to aid in wildlife conservation efforts.
Topics Covered: Data Scraping Data Preprocessing Data Cleaning Data Segmentation GIS Tableau Market Analysis Data Analysis
This was a comprehensive data analysis project that involved various stages. We initiated by scraping data from the web, specifically from PropertyFinder.ae. After gathering the data, we meticulously cleaned and organized it using Python. Additionally, we conducted segmentation to enhance our analysis by categorizing the data in various ways. To further enrich our insights, we incorporated GIS (Geographic Information System) data for more in-depth analysis. Finally, we wrapped up the project by creating interactive dashboards to visualize our findings, making the data easily accessible and comprehensible for presentation purposes.
Topics Covered: Data Collection Data Preprocessing Image Augmentation Transfer Learning Computer Vision Machine Learning
In an era where artificial intelligence (AI) has revolutionized numerous domains, we find ourselves presented with a unique opportunity. What if we could harness the power of AI to enhance our ability to classify and identify birds within this rich tapestry of avian life?
To answer that, we collected images of bird species from the web, encompassing all 42 orders within the Aves class. After preprocessing the data, we trained a model using ResNet101 transfer learning.
Topics Covered: Data Scraping Data Preprocessing Data Cleaning Deep Learning NLP (Natural Language Processing) Machine Learning Transfer Learning Language Model
How much do you know about fan made stories? Did you know about the immense world of fan community where non-professional and semi-professional writers alike showcase their writing ability. Well, I found out about it and thought, why not utilize these data to make a NLP classification model that can learn pattern from fan made stories.
This project showcases the implementation of multi-label text classification using Hugging Face Transformers and Fastai. It involves training a deep learning model to predict multiple genre labels for text descriptions. Key features include web scraping with Selenium Webdriver, data extraction from Royal Road (a fan-made stories website), utilization of pre-trained transformer models, Fastai's text processing capabilities, performance analysis metrics like F1 score and ROC AUC, and detailed code explanations.
Mental Health Volunteer
Dear Camelia
2021-2023
At Dear Camelia, I served as a mental health volunteer on a virtual platform dedicated to providing support to those in need. As first responders, our team was committed to helping individuals seeking assistance and guidance during challenging times.
In addition to our direct support role, we actively contributed to raising awareness about mental health issues. This involved writing informative articles and creating engaging social media posters to promote mental well-being and offer valuable resources to the community.
For any queries or validation, them as described on https://dearcamelia.com/contact-us-en/