Data Source Identification: Supports the understanding of the priority order of requirements and service level agreements. Helps identify the most suitable source for data that is fit for purpose. Performs initial data quality checks on extracted data.
Problem Formulation: Translates business problems within one's discipline to data related or mathematical solutions. Identifies what methods (for example, analytics, big data analytics, automation) would provide a solution for the problem. Shares use cases and gives examples to demonstrate how the method would solve the business problem.
Data Strategy: Understands, articulates, interprets, and applies the principles of the defined strategy to unique, moderately complex business problems that may span one or main functions or domains.
Data Visualization: Identifies and recommends the most suitable visualization tools based on context. Generates appropriate graphical representations of data and model outcomes. Understands customer requirements to design appropriate data representation for complex data sets and drive User Experience designers and User Interface engineers to build front end applications. Defines application design based on customer requirements. Builds compelling stories based on context to integrate multiple pieces of information into cohesive insights. Presents to and influences diverse audiences using the appropriate frameworks and conveys clear messages through deep business and stakeholder understanding. Customizes communication style based on stakeholders and leverages relationships to drive behavioral change. Guides and mentors junior associates on story types, structures, and techniques based on context.
Applied Business Acumen: Evaluates proposed business cases for projects and initiatives. Influences business stakeholder decision making. Translates business requirements into strategies, initiatives, and projects and aligns them to business strategy and objectives and drives the execution of deliverables. Builds and articulates the business case and return on investment and delivers work that has demonstrable value. Challenges business assumptions on topics related to one's domain expertise. Develops new organization-wide processes and ways of working. Teaches and guides others on best practices. Proactively engages in the external community to build Walmart's brand and learns more about industry practices. Data Quality Management: Promotes and educates others on data quality awareness. Profiles, analyzes, and assesses data quality. Tests and validates data quality requirements. Continuously measures and monitors data quality. Delivers against data quality service level agreements. Manages operational Data Quality Management procedures. Manages data quality issues and leads data cleansing activities to remove data quality defects, improves data quality, and eliminates unused data. Determines user accessibility and removes or restricts user access as needed. Interprets company and regulatory policies on data. Educates others on data governance processes, practices, policies, and guidelines.
Exploratory Data Analysis: Promotes the value of Knowledge Discovery in Data (KDD) for business managers. Identifies and applies suitable KDD tool basis business requirement. Guides junior team members on tools and techniques. Stays abreast of best practices in KDD techniques. Tests and evaluates multiple solutions, methods, and models to determine accuracy, validity, and applicability. Establishes standards for application and interpretation of statistical data. Conducts statistical experiments(for example hypothesis tests, confidence intervals) and builds statistical models using packages like Statistical Analysis Systems (SAS). Designs, writes, and publishes numerous research documents on diverse topics. Consults on complex situations to test hypotheses, anticipate pitfalls, prevent false conclusions, and advise others on avoiding them. Provides insights to the business based on research findings.
Drives the execution of multiple business plans and projects by identifying customer and operational needs; developing and communicating business plans and priorities; removing barriers and obstacles that impact performance; providing resources; identifying performance standards; measuring progress and adjusting performance accordingly; developing contingency plans; and demonstrating adaptability and supporting continuous learning.
Promotes and supports company policies, procedures, mission, values, and standards of ethics and integrity by training and providing direction to others in their use and application; ensuring compliance with them; and utilizing and supporting the Open Door Policy.
Ensures business needs are being met by evaluating the ongoing effectiveness of current plans, programs, and initiatives; consulting with business partners, managers, co-workers, or other key stakeholders; soliciting, evaluating, and applying suggestions for improving efficiency and cost-effectiveness; and participating in and supporting community outreach events.
About Global Tech
Imagine working in an environment where one line of code can make life easier for hundreds of millions of people and put a smile on their face. That’s what we do at Walmart Global Tech. We’re a team of 15,000+ software engineers, data scientists and service professionals within Walmart, the world’s largest retailer, delivering innovations that improve how our customers shop and empower our 2.2 million associates. To others, innovation looks like an app, service or some code, but Walmart has always been about people. People are why we innovate, and people power our innovations. Being human-led is our true disruption.
Working virtually this year has helped us make quicker decisions, remove location barriers across our global team, be more flexible in our personal lives and spend less time commuting. Today, we are reimagining the tech workplace of the future by making a permanent transition to virtual work for most of our team. Of course, being together in person is an important part of our culture and shared success. We’ll collaborate in person at a regular cadence and with purpose.
Option 1: Bachelor's degree in Business, Engineering, Statistics, Economics, Analytics, Mathematics, Arts, Finance or related field and 3 years' experience in data analysis, data science, statistics, or related field. Option 2: Master's degree in Business, Engineering, Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 1 year's experience in data analysis, data science, statistics, or related field. Option 3: 5 years' experience in data analysis, data science, statistics, or related field.
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)
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