Senior Data Analyst

Orlando, FL 32801

Posted: 03/11/2019 Industry: Other Area(s) Job Number: 34180


Responsible for performing in-depth analysis to identify actionable business insights, performance gaps and perform root cause analysis. The Sr. Data Analyst will perform in-depth research across a variety of data sources to determine current performance and identify trends and improvement opportunities. Collaborate with leadership and functional business owners as well as other personnel to understand friction points in data that cause unnecessary effort, and recommend gap closure initiatives to policy, process, and system. Serve as a data and analysis coach commission-wide for other data analysts.

  • Lead, create, validate, and implement of statistical models; Diagnose, validate, and improve the performance of these models over time to ensure accuracy, statistical confidence, and business goal alignment;
  • Recommend, promote, and audit best practices related to data usage, reporting standards, dashboard formats, visualization style, and analysis methods;
  • Coach and train data analysts in recommended best practices, new skills, troubleshooting, and communication;
  • Identify trends and actionable insights to inform and enable qualitative and quantitative data-driven decisions across the organization;
  • Communicate significance of statistical findings using business acumen and vernacular common to the utilities industry and lead discussions with stakeholders regarding data, analyses, visualizations, conclusions and recommendations in a manner that influences decisions and outcomes;
  • Collaborate with I.T. and external consultants in decisions related to data modeling, dimensionality, data granularity, fit-for-use architecture, and overall data governance;
  • Perform data mining for new business insights; interpret data; draw conclusions; communicate findings to relevant stakeholders and deep data analysis, research, and studies relative to business discovery use cases;
  • Maintain strong understanding of the company’ s data sources, relationships, and best practice usage;
  • Lead / participate in troubleshooting and debugging efforts;
  • Prepare and present visualizations, dashboards, and reporting, as well as, update data visualizations and dashboards;
  • Lead efforts to perform complex Data Story Telling;
  • Verify information integrity of reports, dashboards, and analysis and identify and escalate data anomalies that might affect accuracy;
  • Generate scheduled and ad hoc reports and documentation related to " reporting and analysis" development, implementation, and support;
  • Perform deep data profiling to gain an understanding of the raw data available for analysis.
  • Perform data mining as part of a data science or machine learning exercise to identify themes and trends for further analysis;
  • Perform routine research and analysis to identify data trends, anomalies, and actionable insights that are applicable to the company

  • Working knowledge of all, but not limited to, the following:
    • Visualization Development - Generate analysis through data visualizations from multiple data sets using standard best-in-class analytics software;
    • Understanding of data modeling in the context of transforming data from an OLTP system to an OLAP or other data warehouse related structure. Understanding of the importance of how data is modeled to support the needs of a data reporting and analysis environment;
    • Processes for leveraging data from data warehousing / data mart / data lake environments;
    • Query complex data structures and derive information for reporting, visualizations, and statistical analysis;
    • Complex Data Story Telling Ability;
    • Experience in a data warehouse / data mart OLAP environment leveraging data in star schemas, snowflake schemas, and similar data structures; o Experience working with a best-in-class DBMS (Oracle, SQL Server, etc.) to extract and transform data for reporting, analysis, and data science;
    • Basic Analytics - Perform basic data analysis to include data profiling, data quality, joining of data tables, graphing, basic trend analysis, data segmentation;
    • Ad Hoc Query Development - Quickly develop, test, and provide ad hoc (one-time) information based on a business request leveraging internal or external data and using standard querying toolsets;
    • Requirements gathering and analysis;
    • SQL - basic query and data manipulation skills including selects, inserts, updates, table joins, complex “ where” statements, grouping, subquery imbedded statements;
    • Visualization (Qlik, PowerBI, Cognos, Tableau) - advanced skills in a best-in-class data visualization tool to include data preparation, rationalization of visualization type, standard charting (time series, Pareto, bar, area, multi-axis, geospatial, scatter plots, etc.), filtering, drill-downs, drill-throughs, navigation, dashboard creation, deep understanding of user interface and effective presentation;
    • Knowledge / application of related industry, organizational, and departmental policies, practices and procedures, legal guidelines, ordinances and laws;
    • Excel - advanced skills including graphing, Pivot Tables, VLOOKUP, multi-sheet references, basic statistical modeling and analysis;
    • Dashboard Development - Gather requirements, identify metrics and goals, leverage data sources, select appropriate dashboard objects, and implement a dashboard using a best-in-class tool;
    • Report Development - Create reports from multiple data sets using standard best-in-class reporting software;
    • Project Management - Facilitate, create, implement, and manage a project or projects using MS Project or a similar project tracking tool; ability to define, document, and communicate a project charter, resource assignments, risks, issues, and status over the course of a project;
  • Familiarity with all, but not limited to, the following:
    • Python - demonstrated examples of deep data analysis and outcomes leveraging Python or similar data science tools;
    • R - demonstrated examples of deep data analysis and outcomes leveraging R or similar data science tools;
    • Machine Learning Algorithm Development;
    • Familiarity with generally accepted data and information privacy standards (GDPR, PCI, PII, HIPAA, etc.);
    • Prescriptive Model Development - Leverage historic internal and external data to generate prescriptive recommendations using appropriate statistical methods and confidence measures;
    • Predictive Model Development - Leverage historic internal and external data to generate predictive business models forecasting trends and providing insights with relevant statistical confidence measures and using appropriate statistical methods;
    • Familiarity with leveraging large data sets for data science, machine learning and related analysis;
    • Experience with unstructured database systems (Hadoop, NoSQL);
    • Process flow documentation;
    • Related industry, organizational and departmental policies, practices and procedures; legal guidelines, ordinances and laws.
  • Ability to:
    • Ability to apply data quality assurance and troubleshooting to data profiling, analysis, and reporting;
    • Ability to apply appropriate data cleansing and transformation techniques to prepare data for reporting and analysis;
    • Identify trends, draw conclusions, and summarize results derived from data analysis to produce business-relevant and actionable conclusions;
    • Transform information into actionable insights;
    • Demonstrate strong analytical ability to identify appropriate analysis, data anomalies, trends, etc.;
    • Advanced presentation skills leveraging appropriate software, adapting to audience, and excellent written and grammatical skills;
    • Work with minimal supervision; self-directed; seeks assistance when needed; o Excellent written and verbal communications skills;
    • Use advanced Microsoft Office Suite (Excel, PowerPoint, Word, Outlook, etc.) and standard office equipment (telephone, computer, copier, etc.);
    • Make arithmetic computations using whole numbers, fractions and decimals, rates, ratios, and percentages;
    • Strong attention to detail.
    • MS Access - (optional) advanced skills including relational table joins, data transformation through joins, filtering, updates, and summarization, reporting;
    • Reporting (Cognos, OBIEE, Crystal) - (optional) advanced skills in standard columnar reporting, requirements gathering, data preparation requirements, report creation, testing, scheduling, and deployment.
  • Education/ Certification/ Years of Experience Requirements:
    • Master’ s degree in Data Science, Statistics, Applied Math, Computer Science, Business, or related field of study from an accredited college or university AND minimum of one (1) year of experience in data analytics OR Bachelor’ s degree in Data Science, Statistics, Applied Math, Computer Science, Business, or related field of study from an accredited college or university
    • Minimum of five (5) years of experience in data analytics, or working in a data analyst environment 
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