Remote: Digital Data Support Engineer

Job Description - Perform complex analytical and statistical modeling on large data sets to support various business operations and organizational objectives. - Define data requirements, perform data collection, processing, cleaning, analysis, modeling and visualization. - Identify data patterns and trends to answer business questions and improve decision making. - Identify opportunities to increase efficiency and automation of data analysis processes and procedures. - Leads the most complex data analysis with minimal supervision and wide latitude for independent judgment. - Individual contributor and mentor to more junior staff. - Design, develop, maintain, and manage highly advanced reporting, dashboards, data models and analytical results of significant impact. - Evaluate and define functional requirements for analytics and business intelligence (BI) solutions - Retrieve, analyze and validate data and test accuracy of reported results. - Work directly with project leads to understand requirements and propose key analytics solutions to drive effective decision-making and influence business objectives. - Produce actionable reports that demonstrate key performance indicators, identify areas of improvement for current operations, and show root cause analysis of problems. - Analyze and summarize business operations, customer and/or economic data in order to improve business intelligence, optimize operating effectiveness and predict business outcomes. - Identify trends and patterns in business data; create data visualizations to support business decision making. - Build new and/or modify existing database/data warehouse/data mart and business intelligence solutions to meet business and system requirements. - Collaborate with business units and senior management to conduct needs assessment to support business unit objectives. - Provides input on highly complex Data Science and Big Data projects. - Effectively communicate findings and insight to stakeholders and provide business strategy recommendations for optimizing business performance. - Lead, guide, and mentor less experienced staff; Direct the work of others as needed. - Perform other duties as assigned.

Qualifications - Master s Degree in a related field, or the equivalent combination of training, education and experience. - Extensive experience in the application of statistical methods, mathematical techniques, forecasting, cost- benefit analysis, related analytical tools and programming languages. - Expert skill interpreting, extrapolating and interpolating data for statistical research and modeling - Extensive experience in problem resolution including determining root cause, scope and scale of issues. - Expert skill analyzing statistics and reports to determine business performance and trends. - Extensive experience that demonstrates the ability to research, compile, and document data, business processes, and workflow. - Expert skill identifying and analyzing business requirements and recommending solutions. - Effective skill presenting findings, conclusions, alternatives, and information clearly and concisely. - Expert knowledge of standard ETL tools and techniques. - Expert knowledge of the process in sourcing raw data and cleansing techniques. - Expert knowledge of emerging trends and influences best practices within discipline. - Advanced knowledge of data warehousing, data cleaning, and other analytical techniques required for data usage. - Expert in understanding and communicating data presented in models, charts, and tables and transforming it into a format that is useful to the business and aids effective decision making. - Expert skill in the use of measurement and statistical practices to analyze current and historical data to make predictions, identify risks, and opportunities enabling better decisions on planned/future events. - Expert in understanding and analyzing models that predict the probability of an outcome - Expert knowledge of and the ability to perform basic statistical analysis such as measures of central tendency, normal distribution, variance, standard deviation, basic tests, correlation, and regression techniques. - Expert skill in collecting and manipulating data used in effective decision making. - Expert knowledge of data models, design tools, business/technical requirements, statistical programming languages, data queries. - Demonstrates a key understanding of multiple database concepts and data flows. - Expert knowledge of various data structures and the ability to extract data sources (such as PySpark, PowerBI). - Advanced knowledge of mapping techniques and data pipelines. - Expert SQL skills. - Advanced verbal and written communication skills. - Advanced database and presentation software skills. - Advanced word processing and spreadsheet software skills.