Associate Analyst, Supply Chain Planning

Job Description:

Roles and Responsibilities

A data analyst is responsible for organizing data related to materials, supply forecast, capacity and the like. They utilize technical expertise to ensure data is accurate and of high-quality. Data is then analyzed, designed, and presented in a way that assists individuals, businesses, and organizations make better decisions.

Activities related to the role, but are not limited to:

Using automated tools to extract data from primary and secondary sources

Removing corrupted data and fixing coding errors and related problems

Performing analysis to assess the quality and meaning of data

Filter Data by reviewing reports and performance indicators to identify and correct code problems

Using statistical tools to identify, analyze, and interpret patterns and trends in complex data sets could be helpful for the diagnosis and prediction

Assigning numerical value to essential business functions so that business performance can be assessed and compared over periods of time.

Preparing reports for the management stating trends, patterns, and predictions using relevant data

Working with programmers, engineers, and management heads to identify process improvement opportunities, propose system modifications, and devise data governance strategies.

Preparing final analysis reports for the stakeholders to understand the data-analysis steps, enabling them to take important decisions based on various facts and trends.

Key Skills for a Data Analyst

Strong mathematical skills to help collect, measure, organize and analyze data

Working knowledge of data science tools such as like SQL, Oracle, R, MATLAB, and Python.

Technical proficiency regarding database design development, data models, techniques for data mining, and segmentation.

Proficiency in statistics and statistical packages like Excel, JMP to be used for data set analyzing

Knowledge of data visualization software like Tableau, QlikView, Power BI

Prompt engineering experience, and working knowledge on use of AI to complement foundations on data science knowledge.

Expertise in domain, database, data tables, data warehouses as key data sources

Problem-solving skills

Accuracy and attention to detail

Adept at queries, writing reports, and making presentations

Collaborative

Verbal and Written communication skills

Proven working experience in data analysis