Data Analyst - Appscript Job

Company Overview
Gamut HR Solutions helps you find the right kind of job! Based in Hyderabad and with a small but dynamic team of 2-10 employees, Gamut HR Solutions is committed to matching the right talent with the right opportunities. For more details, visit our website.

Job Overview
We are seeking a Senior Data Analyst with expertise in Appscript for our Hyderabad location. This full-time position requires a professional with 7 to 10 years of experience. The ideal candidate will have strong data analysis skills and the ability to work effectively within our team.

Qualifications and Skills
Proven experience of 7 to 10 years in data analysis with a solid track record of leveraging data to drive business decisions.
Advanced proficiency in Appscript (Mandatory skill) for automating tasks and handling data within Google Workspace.
Expertise in SQL (Mandatory skill) for database management, querying, and data manipulation.
Strong knowledge of Python for data analysis and automation tasks.
Competence in data visualization tools and techniques to present analytical findings clearly.
Experience in statistical analysis, applying statistical techniques to identify trends and inform decision-making.
Expert in data cleaning, ensuring the accuracy and reliability of data used for analysis.
Excellent problem-solving abilities to identify issues and provide actionable solutions.

Roles and Responsibilities
Analyze complex datasets to extract actionable insights that will inform business strategies and decisions.
Develop and automate processes using Appscript to optimize workflows and reporting within the organization.
Create and maintain SQL queries to manage and manipulate data effectively.
Collaborate with cross-functional teams to understand data requirements and deliver accurate solutions.
Utilize Python for advanced data analysis and automation of repetitive tasks.
Produce detailed and visually appealing reports to communicate findings to stakeholders.
Perform statistical analysis to identify trends and patterns in data.
Ensure data quality and integrity through thorough data cleaning and validation practices.
Troubleshoot and resolve data issues, continually seeking ways to improve data processes and systems.

Information above is Internshala's interpretation and paraphrasing of what we found on the shared link.