(USA) Senior Manager II, Data Analytics

Position Summary...
What you'll do...
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.

• Helping identify the most suitable source for data that is fit for purpose.
• Performing initial data quality checks on extracted data.

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 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 identify and recommend the most suitable visualization tools based on context.

• Generate appropriate graphical representations of data and model outcomes.
• Understand 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.
• Define application design based on customer requirements.
• Build compelling stories based on context to integrate multiple pieces of information into cohesive insights.
• Present to and influence diverse audiences using the appropriate data visualization frameworks and conveys clear messages through deep business and stakeholder understanding.
• Customize communication style based on stakeholders and leverages relationships to drive behavioral change.
• Guide and mentor junior associates on story types, structures, and techniques based on context.

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 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.

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 evaluate proposed business cases for projects and initiatives.

• Translate business requirements into strategies, initiatives, and projects and aligns them to business strategy and objectives and drives the execution of deliverables.
• Build and articulate the business case and return on investment and delivers work that has demonstrable value.
• Challenge business assumptions on topics related to one's domain expertise.
• Mentor the team members on new business insights and allied developments.
• Proactively engage in the external community to build Walmart's brand and learn more about industry practices.

Exploratory Data Analysis
Requires knowledge of:

• 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
• 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
• 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
• 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
• 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
• participating in and supporting community outreach events.

#LI-MF4
Live our Values
Culture Champion

• 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.

Servant Leadership

• Acts as an altruistic servant leader and is consistently humble, self-aware, honest, and transparent.

Embrace Change
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
Customer Focus

• 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.

Strategic Thinking

• 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.

Talent Management

• 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.

Minimum Qualifications...
Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications.
Option 1: Bachelor's degree in Business, Engineering, Statistics, Economics, Analytics, Mathematics, Arts, Finance or related field and 4 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 2 years' experience in data analysis, data science, statistics, or related field. Option 3: 6 years' experience in data analysis, data science, statistics, or related field.
1 year's supervisory experience.
Preferred Qualifications...
Outlined below are the optional preferred qualifications for this position. If none are listed, there are no 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), Supervisory experience
Primary Location...
4650 W NORTH AVE, CHICAGO, IL 60639-4611, United States of America