Analytics role with leading Steel Manufacturing
3 weeks ago
Roles and Responsibilities
Analytics role with leading Steel ManufacturingRoles & Responsibilities:
The position assumes the role of Analytics Officer responsible for Business Reporting and Analytics to modernize MIS, dashboards with focus on actionable insights with the help of data driven decision making. This position will be reporting to Chief Digital Officer and work closely with CXO offices
Technical Must Requirement:
Understating of basic statistical methods, quantitative methods and data analytical approaches in manufacturing domain (Steel/ Metal/ Mining/ Manufacturing) for MIS (Management Information System) and Business Intelligence
Strong understanding of Business Intelligence concepts and the ability to articulate these concepts to business users to modernize reports focusing on actionable insights/ Root cause effect analysis/ variance analysis/ trend analysis/ pareto analysis/ histogram/ Tree map/ Box & whisker/ Waterfall/ chart-pictorial representation for quick data interpretation and decision making. At the same time, person needs to coordinate with the Technology team to develop the same MIS reports/ dashboards.
Stronganalytical skillswith the ability to translate business needs into technical solutions
Must have hands on experience of working on at least one BI reporting and dash boarding tools Power BI, Spotfire, Qlik Sense, Tableu etc.)
Basic understanding of different Data sources (IT: SAP/Non-SAP, OT systems) for developing reports which may need data points from multiple sources basis the business requirement. Understanding of best practices of Data modelling, data warehousing and ETL (Extraction, transform and Load) practices. Knowledge of underlying reporting infrastructure to help scale reporting needs while maintaining high-performance environment for reporting needs
Exposure in Big DataAnalytics and common external data sources. Ability to bring insights from external data sources aligned to internal business processes for better decision making
Application of Machine learning techniques (Supervised and unsupervised) for predication driven decision making.
Strong focus on Data governance approach for reporting requirements
Location:-Gurgaon,Working Model:- Office-
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