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.
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, and apply principles of the defined strategy to routine business problems that involve a single function.
Model Assessment and Validation: Requires knowledge of model fit testing, tuning, and validation techniques (e.g., Chi square, ROC curve, root mean square error etc.); Impact of variables and features on model performance To Identify the model evaluation metrics. Apply best practice techniques for model testing and tuning to assess accuracy, fit, validity, and robustness for multi-stage models and model ensembles.
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 leverages rational arguments. Guide and mentor junior associates on story types, structures, and techniques based on context.
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.
Analytical Modeling: Requires knowledge of feature relevance and selection; Exploratory data analysis methods and techniques; Advanced statistical methods and best-practice advanced modelling techniques (e.g., graphical models, Bayesian inference, basic level of NLP, Vision, neural networks, SVM, Random Forest etc.); Multivariate calculus; Statistical models behind standard ML models; Advanced excel techniques and Programming languages like R/Python; Basic classical optimization techniques (e.g., Newton-Rapson methods, Gradient descent); Numerical methods of optimization (e.g. Linear Programming, Integer Programming, Quadratic Programming, etc.) To select appropriate modeling techniques for complex problems with large scale, multiple structured and unstructured data sets. Select and develop variables and features iteratively based on model responses in collaboration with the business. Conducts exploratory data analysis activities (for example, basic statistical analysis, hypothesis testing, statistical inferences) on available data. Identify dimensions and designs of experiments and create test and learn frameworks. Interpret data to identify trends to go across future data sets. Create continuous, online model learning along with iterative model enhancements. Develop newer techniques (for example, advanced machine learning algorithms, auto ML) by leveraging the latest trends in machine learning, artificial intelligence to train algorithms to apply models to new data sets. Guide the team on feature engineering, experimentation, and advanced modeling techniques to be used for complex problems with unstructured and multiple data sets (for example, streaming data, raw text data).
Model Deployment and Scaling: Requires knowledge of impact of variables and features on model performance; understanding of servers, model formats to store models. To deploy models to production. Continuously log and track model behavior once it is deployed against the defined metrics. Identify model parameters which may need modifications depending on scale of deployment.
Code Development and Testing: Requires knowledge of coding languages like SQL, Java, C++, Python and others; Testing methods such as static, dynamic, software composition analysis, manual penetration testing and others; Business, domain understanding. To write code to develop the required solution and application features by determining the appropriate programming language and leveraging business, technical, and data requirements. Create test cases to review and validate the proposed solution design. Create proofs of concept. Test the code using the appropriate testing approach. Deploy software to production servers. Contribute code documentation, maintain playbooks, and provide timely progress updates.
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: Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 4 years' experience in an analytics related field. Option 2: Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 2 years' experience in an analytics related field. Option 3: 6 years' experience in an analytics or related field
As permitted by applicable law, provide evidence of full vaccination as defined by CDC guidelines OR secure approval of medical or religious accommodation for the vaccination mandate.
Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch)
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