Sfoglia categorie
Esplora
Fiverr Pro
Italiano
$
USD
Kingshuk D
@kingshukdatt175
Data Analyst Data Scientist
Bangladesh
Bengali, Inglese, Hindi
Chi sono
I build data pipelines that help organisations predict what happens next. As a Computer Science graduate with hands-on experience in Python-driven machine learning and analytics, I've worked on real datasets at Janata Bank to build end-to-end ML pipelines, including customer churn prediction and marketing analytics.
Competenze
Kingshuk D
offline •
Consulta i miei servizi
Modello statistico e analisi
I will use python, jupyter and sql for data cleaning and prediction
Portfolio
Esperienza lavorativa
Python with Machine Learning Student
Creative IT Institute
Dec 2025 - Present • 9 mos
Engaged in professional training focused on Python and Machine Learning. Developing foundational and advanced skills in data science workflows, model building, and algorithmic implementation within a structured learning environment at Creative IT Institute.
IT & Data Analyst Intern
Janata Bank • Part time
Jul 2025 - Oct 2025 • 3 mos
• Designed, developed, and tested a Customer Churn Prediction model in Python (Scikit-learn, Pandas), covering the full development lifecycle — coding, validation, and performance evaluation — on real banking data. • Debugged and cleaned a 21-feature banking dataset, identifying and resolving data inconsistencies to improve churn-tracking accuracy by 9%. • Collaborated with internal banking staff and supervisors to troubleshoot and resolve data/query issues, supporting systemic efficiency across 14,323+ customer queries. • Provided Tier-1 technical support, assisting with hardware/software configuration, deployment, and day-to-day IT operations for internal banking systems.
Data Analyst Intern
Excelerate • Part time
Aug 2025 - Sep 2025 • 1 mo
• Performed exploratory data analysis (EDA) and debugging of marketing campaign datasets in Python (Pandas, Matplotlib, Seaborn), identifying and resolving data quality issues prior to analysis. • Authored structured technical documentation translating raw data findings into actionable business recommendations for stakeholders. • Applied data cleaning and transformation techniques to resolve missing values, outliers, and inconsistent formatting across multi-source data, improving tracking methodology accuracy by 5%.
