About
Data Analyst with 1.5 years of experience as a Trainee Decision Scientist, specializing in data collection, analysis, and interpretation from multiple data sources to support business decision-making. Proficient in Python, SQL, Tableau, and Power BI for data automation, analysis, and visualization. Experienced in building dashboards, automating data workflows, and delivering actionable insights. Strong communicator and collaborative team player with a focus on delivering high-quality analytical solutions within deadlines.
Skills & Expertise (26)
Work Experience
Machine Learning Intern
VISAKHAPATNAMSTEELPLANT
May 2023 - Jul 2023
Cleaned and processed large-scale datasets using Python libraries such as pandas and NumPy, ensuring data quality and consistency for analytical modeling. Performed complex data manipulation and transformation to prepare datasets for advanced analysis and machine learning workflows. Created dynamic visualizations and plotted key analytical insights using Matplotlib, effectively communicating trends, patterns, and findings to both technical and non-technical stakeholders. Supported data-driven decision-making by delivering thorough exploratory data analysis and actionable recommendations based on well-illustrated data outputs.
Trainee Decision Scientist
Mu Sigma Inc.
Jul 2024 - Feb 2026
Collaborated on the Fuel Analytical Data Set (ADS) project in the cruise industry, performing advanced fuel data manipulation, large-scale data processing, and foundational data wrangling using Python (Pandas, NumPy) and SQL to support operational analytics. Collected, analysed, and interpreted complex datasets from multiple internal and external data sources, ensuring data accuracy, consistency, and reliability for downstream analytics and business reporting. Designed and maintained interactive Tableau dashboards to monitor key fuel consumption metrics, voyage performance, and operational efficiency, enabling stakeholders to make data-driven decisions. Built predictive fuel forecasting models using regression analysis and Z-score–based anomaly detection, applying intermediate AI/ML concepts to identify fuel consumption trends and optimize resource planning. Utilized SQL for data extraction, transformation, and management of relational databases, performing complex joins, aggregations, and data validation checks to support analytical workflows. Performed data quality checks, exploratory data analysis (EDA), and statistical validation to detect anomalies and improve the reliability of fuel consumption analytics. Automated repetitive data processing and reporting workflows using Python scripts, improving efficiency and reducing manual effort in data preparation tasks. Prepared technical documentation, analytical reports, and presentations to communicate insights and recommendations to cross-functional teams and business stakeholders. Collaborated with data engineers, analysts, and business stakeholders to translate business requirements into analytical solutions, ensuring alignment between technical outputs and operational goals. Applied problem-solving and analytical thinking to optimize data pipelines, improve forecasting accuracy, and support strategic decision-making in fuel consumption management.
Education
Bachelor's degree, Computer Science - GlTAM Deemed University
- 2024 · Afghanistan
