About
Highly analytical Data Analyst with hands-on experience transforming complex datasets into actionable business solutions. Proficient in MS Excel, Python, SQL, and Power BI, with a proven ability to develop predictive models and conduct in-depth customer segmentation analysis. Successfully translated analytical insights into tangible business strategies, demonstrating a strong aptitude for optimizing operations and driving data-driven decision-making.
Work
Summary
Data Analyst Intern responsible for leveraging data to optimize steel production processes and enhance R&D efficiency in a leading steel manufacturing company.
Highlights
Optimized IS2062-250BR steel composition by analyzing large chemical datasets, achieving a 15% increase in tensile strength and 30% improvement in corrosion resistance through targeted alloying element analysis.
Collaborated with cross-functional teams to develop and implement a predictive model using chemical data, resulting in a 30% improvement in production streamlining and overall efficiency.
Automated testing workflows using Python (Pandas, NumPy) and Excel, enabling the processing of over 200 monthly samples and reducing project timelines by 20%.
Designed and built comprehensive data dashboards to monitor material distribution, significantly optimizing R&D resource allocation.
Skills
Programming Languages
Python, SQL.
Machine Learning
Statistical Analysis, Supervised Learning Algorithms, Unsupervised Learning Algorithms, Predictive Modelling.
Data Analysis Libraries
Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn.
Data Tools & Platforms
MS Excel, Power BI, MySQL, Jupyter Notebook.
Soft Skills
Problem Solving, Adaptability, Data Storytelling, Cross-functional Collaboration, Critical Thinking.