Data Analyst

Responsible for performing routine and ad-hoc analysis to identify actionable business insights, and performance gaps and perform root cause analysis.

The 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.

Primary Functions:

• Participate in the creation, validation, and implementation of statistical models.
• Participate in the improvement of the performance of these models over time to ensure accuracy, statistical confidence, and business goal alignment;
• Identify trends and actionable insights to inform and enable qualitative and quantitative data-driven decisions across the organization;
• Participate in the recommendation, promotion, and auditing of best practices related to data usage, reporting standards, dashboard formats, visualization style, and analysis methods;
• Participate in communicating the significance of statistical findings using business acumen and vernacular common to the utility industry;
• Participate in discussions with stakeholders regarding data, analyses, visualizations, conclusions and recommendations in a manner that influences decisions and outcomes;
• Participate in deep data analysis, research, and studies relative to business discovery use cases;
• Collaborate with I.T. and external consultants in decisions related to data modeling, dimensionality, data granularity, fit-for-use architecture, and overall data governance;
• Participate in performing data mining for new business insights; interpret data; draw conclusions; communicate findings to relevant stakeholders;
• Develop a strong understanding of client's data sources, relationships, and best practice usage;
• Lead/participate in troubleshooting and debugging efforts;
• Prepare and present visualizations, dashboards, and reporting;
• Update data visualizations and dashboards;
• Identify and escalate data anomalies that might affect accuracy;
• Verify information integrity of reports, dashboards, and analysis;
• Generate scheduled and ad hoc reports;
• Generate documentation related to "reporting and analysis" development, implementation, and support;
• Participation in deep data profiling efforts to gain an understanding of the raw data available for analysis.
• Participation in data mining efforts as part of a data science or machine learning exercise to identify themes and trends for further analysis;
• Participation in identifying trends, drawing conclusions, and summarizing results derived from data analysis to produce business-relevant and actionable conclusions;
• Participation in transforming information into actionable insights;
• Perform routine research and analysis to identify data trends, anomalies, and actionable insights that are applicable to the client;
• Perform other duties as assigned.

Skills

Technical Requirements:

Working knowledge of all, but not limited to, the following:

• Processes for leveraging data from data warehousing/data mart / data lake environments;
• Visualization Development - Generate analysis through data visualizations from multiple data sets using standard best-in-class analytics software;
• Query complex data structures and derive information for reporting, visualizations, and statistical analysis;
• Requirements gathering and analysis;
• 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;
• Report Development - Create reports from multiple data sets using standard best-in-class reporting software;
• SQL - basic query and data manipulation skills including selects, inserts, updates, table joins, and grouping;
• 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;
• Excel - advanced skills including graphing, Pivot Tables, VLOOKUP, and multi-sheet references;
• Experience working with a best-in-class DBMS (Oracle, SQL Server, etc.) to extract and transform data for reporting, analysis, or data science;

Familiarity with all, but not limited to, the following:

• Familiar with a data warehouse / data mart OLAP environment leveraging data in star schemas, snowflake schemas, and similar data structures;
• Familiar with data modeling in the context of transforming data from an OLTP system to an OLAP or other data warehouse related structure.
• Familiar with the importance of how data is modeled to support the needs of a data reporting and analysis environment;
• Familiarity with generally accepted data and information privacy standards (GDPR, PCI, PII, HIPAA, etc.);
• Familiarity with leveraging large data sets for data science, machine learning, and related 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;
• 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;
• Query Optimization – ability create/modify SQL or other query code to ensure request has minimal impact on the target database and executes in the most efficient manner possible;
• Knowledge / application of related industry, organizational, and departmental policies, practices and procedures, legal guidelines, ordinances and laws;
• 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;
• 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;
• Demonstrate strong analytical ability to identify appropriate analysis, data anomalies, trends, etc.;
• Advanced presentation skills leveraging appropriate software, adapting to the audience, and excellent written and grammatical skills;
• Work with minimal supervision; self-directed; seeks assistance when needed;
• Excellent written and verbal communication 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 - advanced skills including relational table joins, data transformation through joins, filtering, updates, and summarization, reporting (preferred);
• Reporting (Cognos, OBIEE, Crystal) - advanced skills in standard columnar reporting, requirements gathering, data preparation requirements, report creation, testing, scheduling, and deployment. (preferred)

Experience

• Bachelor’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 three (3) years of experience in data analytics, or working in a data analyst environment.

Education

• Bachelor’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 three (3) years of experience in data analytics, or working in a data analyst environment.