Data Analyst II

Position Summary...

What you'll do...

Understanding Business Context Requires knowledge of Industry and environmental factors Common business vernacular Business practices across two or more domains such as product finance marketing sales technology business systems and human resources and indepth knowledge of related practices Directly relevant business metrics and business areas To Support the development of business cases and recommendations Drive delivery of project activity and tasks assigned by others Support process updates and changes Support under guidance in solving business issues

Data Source Identification Requires knowledge of Functional business domain and scenarios Categories of data and where it is held Business data requirements Database technologies and distributed data stores eg SQL No

SQL Data Quality Existing business systems and processes including the key drivers and measures of success To Understand the appropriate data set required to develop simple models by developing initial drafts Support the identification of the most suitable source for data Maintains awareness of data quality

Tech Problem Formulation Requires knowledge of Analytics big data analytics automation techniques and methods Business understanding Precedence and use cases Business requirements and insights To Identify possible options to address the business problems within ones discipline through relevant analytical methodologies Demonstrate understanding of use cases and desired outcomes

Data Visualization Requires knowledge of Visualization guidelines and best practices for complex data types Multiple data visualization tools for example Python R libraries GGplot Matplotlib Ploty Tableau PowerBI etc Advanced visualization techniques tools Multiple story plots and structures OABCDE Communication influencing technique Emotional intelligence To Generate appropriate graphical representations of data and model outcomes Understand customer requirements to design appropriate data representation for multiple data sets Work with User Experience designers and User Interface engineers as required to build front end applications Present to and influence the team and business audience using the appropriate data visualization frameworks and conveys clear messages through business and stakeholder understanding Customize communication style based on stakeholder under guidance and leverage rational arguments Guide and mentor junior associates on story types structures and techniques based on context

Data Quality Management Requires knowledge of Data quality management techniques and standards Business metadata definitions and content data definitions Data profiling tools data cleansing tools data integration tools and issues and event management tools Understanding of users data consumption data needs and business implications Data modeling storage integration and warehousing Data quality framework and metrics User access best practices Enterprise data architecture modeling and design storage integration and warehousing Enterprise data quality framework and metrics Enterprise data strategy Enterprise data quality strategy Enterprise strategy to address regulatory and ethical requirements and policies around data privacy security storage retention and documentation To Promote data quality awareness Profile analyze and assess data quality Test and validate data quality requirements under supervision of others Execute operational Data Quality Management procedures under supervision of others Conduct data cleansing activities to remove data quality defects improve data quality and eliminate unused data under supervision of others Grant user access to data Learn company and regulatory policies on data Learn data governance processes practices policies and guidelines

Exploratory Data Analysis Requires knowledge of relevant Knowledge Discovery in Data KDD tools applications or scripting languages such as SQL Oracle Apache Mahout MS Excel Python Statistical techniques for example mean mode median variance standard deviation correlation and sorting and grouping Research analysis standards and activities Documentation procedures…