The Data Analyst will provide support to the Data and Analytics Officer in analyzing key business processes and recommend how different types of data can be used to improve them. The associate is aimed to aid with/do research and analyses, communicate their insights, both in writing and verbally.
The Data Analyst is expected to work with different business units together with the Data & Analytics Officer in transforming business requirements to data assets which can provide valuable insight, predictions and actionable advice to our stakeholders and at the same time help in Data and Analytics Solutions’ strategies, organizations, planning, and technologies. Moreover, the Data Analyst will also support broader endeavors from a data and analytics perspective.
Responsibilities: Provide support in data and analytics endeavors of Coal BU. This include working with other subsidiaries' data science teams to create a prioritized list of needs for each business segment. Collaborate in implementing statistical methods to analyze data and generate useful recommendations to new ways on how we can improve existing business processes. Shares best practices, lessons learned and constantly updates the team on changing technologies, and knowledge related to recent, current and upcoming vendor products and solutions. Ability to apply conceptual models, recognize patterns, draw and defend conclusions with peer analysts and stakeholders. Ability to provide a good understanding of both technology and industry that includes Data and Analytics vendors, products and strategies. Recommends and participates in the design and implementation of standards, tools, and methodologies Minimum Qualifications:
At least 2-year experience in analytics related field; Minimum of Bachelor of Science Degree (Computer Science, Information Technology, Mathematics, or any related courses); Rigorous understanding for areas such as Mathematics and Computer Programming; Familiarity regarding data models, database design development, data mining and segmentation techniques; Adept with data visualization, data exploration and analysis, business intelligence techniques, and with a keen attention to details; Familiarity with latest Data Science tools and platforms