Reliability Data Analyst

LTTS India

Vadodara

A Reliability Data Analyst is a key player in managing performance through key performance indicators
(KPIs). Their responsibiliƟes include collecƟng, verifying, and analyzing vast amounts of equipment and process performance data. They input, raƟonalize, and calculate KPIs for review and performance improvement discussions. Beyond understanding historical events, their focus extends to forecasƟng future occurrences. They extract valuable insights that drive growth, efficiency, and innovaƟon. Key responsibiliƟes and skills: 1. Monthly Data CollecƟon and Cleaning:  Collect and clean data to develop KPI dashboards and trending reports for decision-making.  UƟlize staƟsƟcal analysis, data visualizaƟon, and machine learning techniques to analyze trends and provide commentary highlights. 2. Business Improvement:  Assist in data collecƟon and interpretaƟon to support opƟmizaƟon, risk management, and business planning. 3. SME and Administrator of Engineering SoŌware ApplicaƟons:  Appointed SME and administrator for departmental soŌware applicaƟons.  Act as a user help desk for queries and troubleshooƟng. 4. MOCs RCM Focal:  Conduct new equipment RCM studies for MOCs and small projects. 5. Specific Tasks:  Serve as the document focal point for reliability documentaƟon, ensuring Ɵmely updates of procedures. Skills set for a Reliability Data Analyst Technical Skills:  Data Management: A strong foundaƟon in data management and database systems is essenƟal.  StaƟsƟcal Analysis: Understand staƟsƟcal concepts and methods for analyzing reliability data.  Data VisualizaƟon: Ability to create clear and informaƟve visualizaƟons to communicate insights.  Programming Languages: Knowledge in Python, R, and SQL, Access  Excel Proficiency: Solid numerical skills and familiarity with querying languages2. SoŌ Skills:  AnalyƟcal Thinking: Strong problem-solving skills to idenƟfy and resolve data quality issues effecƟvely.  CommunicaƟon: Excellent communicaƟon skills for explaining data insights and collaboraƟng with stakeholders.  Interpersonal Skills: Building relaƟonships and working effecƟvely with cross-funcƟonal teams.

Data analysis, Asset management