Data Analyst IIThe Data Analyst II works with industry data to identify and communicate insights that help internal and industry partners make data-driven decisions and rules. In addition, the Data Analyst II works with Product Managers to analyze and understand customers’ business problems, translate them into requirements for development, and coordinate acceptance and launch of solutions that solve those problems in a compelling way.Job Accountability/Responsibilities:Essential Functions – Subject Matter Expert (65%): Independently perform exploratory analysis and develop reports/dashboards that clearly communicate findings given the business context.Work closely with customers, internal and external, to understand the sources of data, the definition of data elements, and the quality of data being captured or analyzed.Work to identify key issues and develop metrics that can quantify them appropriately.Work with business stakeholders to identify value adding analytical opportunitiesPrepare analyses to highlight discrepancies in datasets and recommend approaches for managing them.Develop data analysis tools to assist in understanding and solving business problemsEssential Functions – Product Performance/Service Analysis (20%): Analyze product usage and performance for maintenance prioritization and compliance with service level agreementsCommunicate with IT department as appropriateCreate and document repeatable solutions for ongoing customer requirements and legacy product responsibilitiesEnsure information delivered to customers meets Data Access policiesEssential Functions – Mentoring (10%): Provide guidance to less experienced team members and share learning on new skills and techniques with all team membersNon-Essential Functions:Lead development of clear business value propositions.Independently conduct market research and assessments of opportunities.Other duties as assignedKnowledge, Skills, abilities/minimum requirements/competencies:Ability to manage multiple activities in a deadline-oriented environment; highly organized and flexibleStrong research skills with an attention to detailAbility to explain complex findings and approaches to un-technical audiences, including effective communication through visualizations.Proficient in SQLExperience in analysis using descriptive and predictive statistics and advanced statistical techniques such as forecasting, sampling techniques, multiple regression analysis, and basic machine learning algorithms.