Data Analyst

Company Overview

Our motto "Growth is Life" aptly captures the ever-evolving spirit of Reliance. Our activities span hydrocarbon exploration and production, petroleum refining and marketing, petrochemicals, retail, and telecommunications. We are committed to innovation-led, exponential growth, achieving global leadership in many areas, including as the largest polyester yarn and fiber producer in the world. A Fortune 500 company, Reliance Industries Limited is the largest private sector corporation in India. Our headquarters are located in Navi Mumbai, Maharashtra.

Job Overview

We are seeking a mid-level Data Analyst to join our team in Jamnagar. This is a full-time position that involves utilizing statistical tools and programming languages to analyze data sets, interpret trends, and provide actionable insights to drive business decisions. The ideal candidate will have proficiency in statistical analysis, Python programming, and data visualization.

Qualifications And Skills

• Proficiency in statistical analysis (Mandatory skill)
• Strong knowledge of Python programming for data analysis purposes (Mandatory skill)
• Experience with data visualization tools such as Tableau or Power BI (Mandatory skill)
• Experience in machine learning and its applications in data analysis
• Ability to develop predictive models to forecast business metrics
• Experience working with big data technologies and platforms
• Proficiency in SQL for data querying and manipulation
• Experience in data mining and transforming raw data into useful business insights
  
  

Roles And Responsibilities

• Analyze large data sets using statistical techniques
• Identify trends, patterns, and anomalies within data to provide actionable insights
• Develop, implement and maintain automated reporting processes
• Collaborate with cross-functional teams to understand business requirements and provide data-driven solutions
• Create and maintain documentation for data analysis processes and methodologies
• Assist in the design and implementation of data models and data mining techniques
• Communicate complex data findings to non-technical stakeholders in an understandable way
• Support continuous improvement initiatives by providing data-based recommendations for processes and operations