About
Data Aanlyst
- Email: ekramml0013@gmail.com
- Website: AnalyzerEkram.tech
- City: Erlangen, Germany
- Degree: M.Sc. in Data Science
A hardworking Individual who would like to do things with perfection and within the deadline. I am a person with Excellent problem-solving skills and the ability to perform well in a team. Passionate about coding and enjoy exploring more about ML and AI. I also worked as a Research Assistant in the field of Data Science. Apart from this, I am a person who is always ready to develop new skills and grow knowledge by gaining practical experience. An intelligent Student Worker with distinguished knowledge of Research, MachineLearning Model Development, and Data Visualization with Microsoft Power BI. Fantastic attention to detail with training in Open-Source-platform Github and extensive knowledge of Microsoft Azure Services. Along with these, I have six international publications that solve multiple problems and help to develop new technologies. Recently working with Mortality of Covid-19 patient.
Skills
Languages
Python
Java
C
JavaScript
HTML
CSS
Frameworks & Tools
Flask
Scikit-Learn
Numpy
Matplotlib
Tensorflow
Keras
Power BI
Microsoft Excel
Git
MySQL
Google Colab
Jupiter Notebook
Operating Systems
MacOS
Linux
Windows
Resume
Work Experience
Working Student - Data Analyst
Sep 2022 - March 2024
Elektrobit Automotive GmbH
- Led the development of an automated report generation system, consolidating data from 7+ disparate sources to streamline daily tracking operations, resulting in a 50% reduction in manual tracking time for QA teams and developers.
- Collaborated with cross-functional teams to customize and optimize the reporting system, achieving a notable 40% increase in operational efficiency organization-wide.
- Track Jenkins build information, including pass or fail statuses, providing comprehensive insights into project progress by generated reports.
- Implemented a structured SQL database to methodically store and analyze daily Klocwork project data, ensuring steadfast data integrity.
- Continuously monitored and optimized the performance of the database infrastructure, achieving a 15% increase in data processing speed by identifying and addressing potential bottlenecks.
- Technologies Used: Python, Jenkins, Github, Klocwork, Azure SQL Database, Microsoft Power BI.
Research Assistant
Sep 2019 - March 2021
Daffodil International University
- Conducting literature searches
- Data management, Maintaining data collection files and assisting with data analysis
- Generating correspondence, Reports and Graph.
Teacher Assistant
April 2019 - December 2021
Daffodil International University
- Work with the lead teacher to monitor the class schedule.
- Assist teachers with lesson preparation by getting materials ready and setting up equipment.
- Collaborate with lead teachers to recognize issues students are facing and recommend solutions.
Education
M.Sc. in Data Science
2021 - Present
Friedrich Alexander University Erlangen–Nürnberg, Germany
B.Sc. in Software Engineering
2017 - 2021
CGPA: 3.87
Daffodil International University, Bangladesh
Higher Secondary Certificate
2014 - 2016
GPA: 4.83
BAF Shaheen College, Bangladesh
Extracurricular Acitvities
SWE Club Research Secretary
July 2018 - December 2021
Department of SWE, DIU
Organise research teams meetings, prepare agendas, take minutes, follow up on action points.
Member of DIU Data Science Lab
April 2020 - Present
Quantative Research Community, DIU
After Joining DDL as a member planned many events and managed the events from backend,and also published numerous scientific papers
Projects
- All
- Power BI Dashboard
- Deep Learning
- Machine Learning
- Software
Publicaitons
Context-Based News Headlines Analysis: A Comparative Study of ML and DL Algorithms
Vietnam Journal of Computer Science
See Publication
A Proficient Model to Classify Bangladeshi Bank Notes for Automatic Vending Machine
ICCCNT 2020 - IEEE
See Publication
Classification of Immunity Booster Medicinal Plants Using CNN: A DeepLearning Approach
ICACDS 2021 - Springer
See Publication
A Proficient DeepLearning Approach to Classify the Usual Military Signs by CNN
IC3 2020 - Springer
See PublicationCertifications