Senior Manager, Data Science

Walmart•Sunnyvale, CA

7d•$143,000 - $286,000•Onsite

About The Position

This role focuses on leveraging data science, machine learning, and advanced analytical modeling to solve complex business problems. The Senior Manager will be responsible for developing and deploying models, communicating insights through data visualization, and guiding junior associates. The position requires a deep understanding of business context, analytical modeling techniques, model deployment, code development, and data strategy. The ideal candidate will contribute to creating inclusive digital experiences and ensuring accessibility in products and services.

Requirements

Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 5 years' experience in an analytics related field.
Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 3 years' experience in an analytics related field.
7 years' experience in an analytics or related field.
Knowledge of model fit testing, tuning, and validation techniques (e.g., Chi-square, ROC curve, root mean square error).
Knowledge of Visualization guidelines and best practices for complex data types.
Knowledge of industry and environmental factors, common business vernacular, and business practices across two or more domains.
In-depth knowledge of related practices and directly relevant business metrics and business areas.
Knowledge of feature relevance and selection, exploratory data analysis methods and techniques, advanced statistical methods, and best-practice advanced modeling techniques (e.g., graphical models, Bayesian inference, basic NLP, Vision, neural networks, SVM, Random Forest).
Knowledge of multivariate calculus, statistical models behind standard ML models, advanced Excel techniques, and programming languages like R/Python.
Knowledge of basic classical optimization techniques (e.g., Newton-Rapson methods, Gradient descent) and numerical methods of optimization (e.g., Linear Programming, Integer Programming, Quadratic Programming).
Knowledge of the impact of variables and features on model performance and understanding of servers and model formats to store models.
Knowledge of coding languages like SQL, Java, C++, Python, and others.
Knowledge of testing methods such as static, dynamic, software composition analysis, and manual penetration testing.
Knowledge of Analytics/big data analytics, automation techniques and methods.
Knowledge of business understanding, precedence and use cases, business requirements and insights.
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).
Knowledge of data quality, existing business systems and processes, including key drivers and measures of success.
Knowledge of understanding of business value and relevance of data and data-enabled insights/decisions.
Knowledge of 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.

Nice To Haves

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
Supervisory experience
Using open source frameworks (for example, scikit learn, tensorflow, torch)
Creating inclusive digital experiences, demonstrating knowledge in implementing Web Content Accessibility Guidelines (WCAG) 2.2 AA standards, assistive technologies, and integrating digital accessibility seamlessly.
Knowledge of accessibility best practices and joining Walmart in creating accessible products and services following Walmart’s accessibility standards and guidelines for supporting an inclusive culture.

Responsibilities

Assess and validate models using techniques like Chi-square, ROC curve, and root mean square error.
Identify the impact of variables and features on model performance.
Apply best practice techniques for model testing and tuning to assess accuracy, fit, validity, and robustness for multistage models and model ensembles.
Generate appropriate graphical representations of data and model outcomes using various visualization tools.
Understand customer requirements to design appropriate data representation for multiple data sets.
Work with User Experience designers and User Interface engineers to build front-end applications.
Present to and influence the team and business audience using appropriate data visualization frameworks.
Customize communication style based on stakeholder needs and leverage rational arguments.
Guide and mentor junior associates on data visualization techniques.
Provide recommendations to business stakeholders to solve complex business issues.
Develop business cases for projects with projected return on investment or cost savings.
Translate business requirements into projects, activities, and tasks aligned with overall business strategy.
Serve as an interpreter to connect business needs with tangible solutions and results.
Identify and recommend relevant business insights pertaining to their area of work.
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.
Conduct exploratory data analysis activities, including basic statistical analysis, hypothesis testing, and statistical inferences.
Identify dimensions and design experiments, and create test and learn frameworks.
Interpret data to identify trends across future data sets.
Create continuous online model learning and iterative model enhancements.
Develop newer techniques, such as advanced machine learning algorithms and auto ML, by leveraging the latest trends in machine learning and artificial intelligence.
Guide the team on feature engineering, experimentation, and advanced modeling techniques.
Deploy models to production.
Continuously log and track model behavior once deployed against defined metrics.
Identify model parameters that may need modifications depending on the scale of deployment.
Write code to develop required solutions 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 code using the appropriate testing approach.
Deploy software to production servers.
Contribute code documentation, maintain playbooks, and provide timely progress updates.
Analyze the business problem within one's discipline and question assumptions to help the business identify the root cause.
Identify and recommend approaches to resolve business problems and create effective technology-focused solutions.
Set relevant deliverables based on established success criteria and define key metrics to measure progress and effectiveness of the solution.
Quantify business impact.
Understand the priority order of requirements and service level agreements.
Define and identify the most suitable sources for required data that is fit for purpose.
Perform initial data quality checks on extracted data.
Review the deliverables of junior associates and provide guidance on data source and quality.
Understand, articulate, interpret, and apply the principles of the defined data strategy to business problems.
Drive the execution of business plans and projects by identifying needs, developing plans, removing barriers, providing resources, measuring progress, and adjusting performance.
Provide supervision and development opportunities for associates by selecting, training, mentoring, assigning duties, building a team, establishing expectations, conducting performance evaluations, and providing recognition.
Promote and support company policies, procedures, mission, values, and standards of ethics and integrity.
Ensure business needs are met by evaluating the effectiveness of current plans, consulting with business partners, and identifying opportunities for improvement.
Create a discipline and focus around developing talent through feedback, coaching, mentoring, and developmental opportunities.
Build strong and trusting relationships with team members and business partners.
Act with integrity, maintaining the highest standards of ethics and compliance.
Follow the law, code of conduct, and company policies.
Act as an altruistic servant leader, being humble, self-aware, honest, and transparent.
Deliver expected business results while putting the customer/member first.
Adopt a holistic perspective when making plans and shaping strategy.
Consistently raise the bar and seek to improve, demonstrating curiosity and a growth mindset.
Seek and implement continuous improvements and encourage the team to leverage new digital tools and ways of working.
Create inclusive digital experiences and ensure accessibility in products and services.

Benefits

Medical, vision and dental coverage
401(k)
Stock purchase
Company-paid life insurance
PTO (including sick leave)
Parental leave
Family care leave
Bereavement
Jury duty
Voting
Short-term and long-term disability
Company discounts
Military Leave Pay
Adoption and surrogacy expense reimbursement
PTO and/or PPTO that can be used for vacation, sick leave, holidays, or other purposes.
Walmart-paid education benefit program (Live Better U) for full-time and part-time associates, covering tuition, books, and fees for programs ranging from high school completion to bachelor's degrees, including English Language Learning and short-form certificates.
Performance-based bonus awards