Data Analyst II

Position Summary

What you'll do...

Understanding Business Context

• 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
• In-depth knowledge of related practices
• Directly relevant business metrics and business areas
• To support the development of business cases and recommendations
• To drive delivery of project activity and tasks assigned by others
• To support process updates and changes
• To support under guidance in solving business issues

Data Source Identification

• Knowledge of Functional business domain and scenarios
• Categories of data and where it is held
• Business data requirements
• Database technologies and distributed datastores eg SQL NoSQL
• 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
• To support the identification of the most suitable source for data
• To maintain awareness of data quality

Tech Problem Formulation

• 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 one's discipline through relevant analytical methodologies
• To demonstrate understanding of use cases and desired outcomes

Data Visualization

• Knowledge of Visualization guidelines and best practices for complex data types
• Multiple data visualization tools for example Python, R libraries, GGplot, Matplotlib, Plotly, Tableau, PowerBI etc
• Advanced visualization techniques tools
• Multiple story plots and structures
• To generate appropriate graphical representations of data and model outcomes
• To understand customer requirements to design appropriate data representation for multiple data sets
• To work with User Experience designers and User Interface engineers as required to build front end applications
• To present to and influence the team and business audience using the appropriate data visualization frameworks and convey clear messages through business and stakeholder understanding
• To customize communication style based on stakeholder guidance and leverage rational arguments
• To guide and mentor junior associates on story types, structures, and techniques based on context

Data Quality Management

• 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
• To profile, analyze, and assess data quality
• To test and validate data quality requirements under supervision of others
• To execute operational Data Quality Management procedures under supervision of others
• To conduct data cleansing activities to remove data quality defects, improve data quality, and eliminate unused data under supervision of others
• To grant user access to data
• To learn company and regulatory policies on data
• To learn data governance processes, practices, policies, and guidelines
• To conduct exploratory Data Analysis
• To support identification and application of statistical techniques based on requirements
• To apply suitable techniques under direction from leadership
• To support data collection and evaluation
• To explore data using simple tools
• To execute existing statistical models and explain how they relate to a client's situation
• To analyze data and compute descriptive statistics that identify trends, outliers, and correlations
• To demonstrate up-to-date expertise and apply this to the development, execution, and improvement of action plans by providing expert advice and guidance to others in the application of information and best practices, supporting and aligning efforts to meet customer and business needs, and building commitment for perspectives and rationales
• To provide and support the implementation of business solutions by building relationships and partnerships with key stakeholders, identifying business needs, determining and carrying out necessary processes and practices, monitoring progress and results, recognizing and capitalizing on improvement opportunities, and adapting to competing demands, organizational changes, and new responsibilities
• To model compliance with company policies and procedures and support Walmart's goal of becoming a regenerative company by making a positive impact for associates, customers, and the world around us, eg, creating a sense of belonging, eliminating waste, participating in local giving
• To act with integrity, maintaining and promoting the highest standards of integrity, ethics, and compliance, modeling the Walmart values and leading by example to foster our culture, supporting Walmart's goal of becoming a regenerative company by making a positive impact for associates, customers, and the world around us, eg, creating a sense of belonging, eliminating waste, participating in local giving
• To serve our customers and members, delivering results while putting the customer/member first, and applying an omnichannel mindset and acting with an Every Day Low Price mindset to drive value and Every Day Low Prices for customers/members
• To strive for excellence, raising the bar and seeking to improve, demonstrating curiosity and a growth mindset, seeking feedback, asking thoughtful questions, supporting innovation and intelligent risk-taking, exhibiting resilience in the face of setbacks, implementing and supporting continuous improvements, and willingly embracing new digital tools and ways of working

Benefits

• Competitive pay
• Performance-based bonus awards
• Additional benefits include:
• Health benefits (medical, vision, and dental coverage)
• Financial benefits (401(k), stock purchase, company-paid life insurance)
• Paid time off benefits (PTO, sick leave, parental leave, family care leave, bereavement, jury duty, voting)
• Other benefits (short-term and long-term disability, company discounts, military leave pay, adoption and surrogacy expense reimbursement, etc.)

Minimum Qualifications

• Option 1: Bachelor's degree in Business, Engineering, Statistics, Economics, Analytics, Mathematics, Arts, Finance or related field
• Option 2: 2 years' experience in data analysis, data science, statistics, or related field.

Preferred Qualifications

• Data science, data analysis, statistics, or related field
• Master’s degree in Business, Computer Science, Engineering, Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field
• Related industry experience (for example, retail, merchandising, healthcare, eCommerce)
• Successful completion of assessments in data analysis and Business Intelligence tools and scripting languages (for example, SQL, Python, Spark, Scala, R, Power BI, or Tableau)