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 datastores (e.g. SQL, NoSQL); Data Quality; Existing business systems and processes, including the key drivers and measures of success. To support the understanding of the priority order of requirements and service level agreements. Help identify the most suitable source for data that is fit for purpose. Perform initial data quality checks on extracted data.
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 in-depth knowledge of related practices; Directly relevant business metrics and business areas. To Provide recommendations to business stakeholders to solve complex business issues. Develop business cases for projects with a projected return on investment or cost savings. Translate business requirements into projects, activities, and tasks and aligns to overall business strategy and develops domain specific artifact. Serve as an interpreter and conduit to connect business needs with tangible solutions and results. Identify and recommend relevant business insights pertaining to their area of work.
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 translate/ co-own business problems within one's discipline to data related or mathematical solutions. Identify appropriate methods/tools to be leveraged to provide a solution for the problem. Share use cases and gives examples to demonstrate how the method would solve the business problem.
Data Strategy: Requires knowledge of understanding of business value and relevance of data and data enabled insights / decisions; Appropriate application and understanding of data ecosystem including Data Management, Data Quality Standards and Data Governance, Accessibility, Storage and Scalability, etc.; Understanding of the methods and applications that unlock the monetary value of data assets. To Understand, articulate, interpret, and apply the principles of the defined strategy to unique, moderately complex business problems that may span one or main functions or domains.
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 influences 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 leverages 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 user's 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 and educate others on data quality awareness. Profile, analyze, and assess data quality. Test and validate data quality requirements. Continuously measure and monitor data quality. Deliver against data quality service level agreements. Manage operational Data Quality Management procedures. Manage data quality issues and leads data cleansing activities to remove data quality defects, improve data quality, and eliminate unused data. Determine user accessibility and removes or restricts user access as needed. Interpret company and regulatory policies on data. Educate others on 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 such as drafting, editing, Bibliography format; Relevant Knowledge Discovery in Data (KDD) tools, applications, or scripting languages such as SQL, DB, SAS, Oracle, Apache Mahout, MS Excel, Python; KDD industry best practices and emerging trends. To collect and tabulate data and evaluate results to determine accuracy, validity, and applicability. Support the identification and application of statistical techniques based on requirements. Apply suitable technique under direction from leadership. Assist in the planning, design and implementation of an exploratory data analysis research projects. Understand existing statistical models and identify and recommend statistical models based on hypothesis. Use advanced Knowledge in Data Discovery tools to write queries and analyze data to identify patterns, trends, outliers, and correlations. Conduct statistical analysis (for example hypothesis tests, confidence intervals) and build basic statistical models using relevant packages/software suites. 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.
Provides supervision and development opportunities for associates by selecting and training; mentoring; assigning duties; building a team-based work environment; establishing performance expectations and conducting regular performance evaluations; providing recognition and rewards; coaching for success and improvement; and ensuring diversity awareness.
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 costeffectiveness; and participating in and supporting community outreach events.
Live our Values
• Models the Walmart values to foster our culture; holds oneself and others accountable; and supports Walmart’s commitment to communities, social justice, corporate social responsibility, and sustainability; maintains and promotes the highest standards of integrity, ethics and compliance.
• Acts as an altruistic servant leader and is consistently humble, self-aware, honest, and transparent.
Curiosity & Courage
• Demonstrates curiosity and a growth mindset; fosters an environment that supports learning, innovation, and intelligent risk-taking; and exhibits resilience in the face of setbacks.
Digital Transformation & Change
• Seeks and implements continuous improvements and encourages the team to leverage new digital tools and ways of working.
Deliver for the Customer
• Delivers expected business results while putting the customer first and consistently applying an omni-merchant mindset and the EDLP and EDLC business models to all plans.
• Adopts a holistic perspective that considers data, analytics, customer insights, and different parts of the business when making plans and shaping the team’s strategy.
Focus on our Associates
Diversity, Equity & Inclusion
• Identifies, attracts, and retains diverse and inclusive team members; builds a high-performing team; embraces diversity in all its forms; and actively supports diversity goal programs.
Collaboration & Influence
• Builds strong and trusting relationships with team members and business partners; works collaboratively and cross-functionally to achieve objectives; and communicates with energy and positivity to motivate, influence, and inspire commitment and action.
• Creates a discipline and focus around developing talent, promotes an environment allowing everyone to bring their best selves to work, empowers associates and partners to act in the best interest of the customer and company, and regularly recognizes others’ contributions and accomplishments.
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), Supervisory experience
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