Company Overview

Scott International is a leading apparel manufacturing unit specializing in T-shirts and corporate attire. With a team of 201-500 employees, we are headquartered in Bangalore, Karnataka. We are proud to be a part of the Apparel Manufacturing industry, delivering high-quality apparel products to our customers. Visit our website at www.scottinternational.com to learn more about us.

Job Overview

We are seeking a skilled Microsoft Excel Specialist to join our team in Bengaluru. This is a mid-level, full-time position requiring 4 to 6 years of work experience. The ideal candidate will possess strong skills in data analysis and statistical analysis, with a proficient understanding of various Excel functionalities.

Qualifications and Skills

• Proven work experience of 4 to 6 years in data analysis and statistical analysis (Mandatory skill).
• Proficiency in using Microsoft Excel for data visualization and analysis.
• Strong capability in predictive modeling and statistical techniques.
• Experience with Python programming for data manipulation and analysis.
• Knowledge in big data tools and techniques for data mining applications.
• Expertise in VLOOKUP and other advanced Excel functions for data retrieval.
• Ability to interpret and visualize data to communicate insights effectively.
• Hands-on experience in data cleaning and preparation for analysis.

Roles and Responsibilities

• Analyze and interpret complex data sets to provide actionable insights.
• Develop and maintain Excel-based models for various business functions.
• Use statistical tools to identify, analyze, and interpret trends or patterns in data sets.
• Create data visualizations using Excel to support business decision-making processes.
• Collaborate with different departments to understand their data-related needs and deliver solutions.
• Perform data validation and quality checks to ensure accuracy and reliability of data.
• Provide training and support to staff on data management and analysis best practices.
• Continuously evaluate and improve existing processes and models to enhance efficiency.