Why you should apply for a job with Walmart:
- 51%of reviewers say women and men are treated equally at Walmart.
What you'll do...
The Walmart Global Tech Merchant Data Science team is looking for a versatile Principal Data Scientist to focus on building complex, cutting edge, and scalable algorithms for our merchandising organization. We are shaping the future of retail and are ready to work closely with merchants to solve their problems!
A Principal Data Scientist is responsible for collaborating with a business segment to determine long-term vision and provide analytical support and guidance. A Principal Data Scientist analyzes large data sets to develop multiple, complex custom models and algorithms to drive innovative business solutions and works on large project teams in order to provide analytical support and guidance to a large project team (for example, email targeting, business optimization, consumer recommendations) within Walmart eCommerce.
The algorithms built by the Principal Data Scientist will be tested, validated, and applied to large data sets. Principal Data Scientists are responsible for training algorithms so they can be applied to future data sets and provide the appropriate search results. Principal Data Scientists are responsible for researching new trends in the industry and utilizing up-to-date technology (for example, HBase, MapReduce, LAPack, Gurobi) and analytical skills.
Data Source Identification:
- Understands the priority order of requirements and service level agreements.
- Defines and identifies the most suitable sources for required data that is fit for purpose, referring to external sources as required.
- Performs initial data quality checks on the extracted data.
- Reviews the deliverables of junior associates and provides guidance.
- 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.
- Analyzes the business problem within one's discipline and questions assumptions to help the business identify the root cause.
- Identifies and recommends approach to resolve the business problem.
- Sets data analytics, big data analytics, automation goals, and deliverables based on the established success criteria and define key metrics to measure progress and effectiveness of the solution.
- Quantifies business impact.
- Selects appropriate modeling techniques for complex problems with large scale, multiple structured and unstructured data sets.
- Selects and develops 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.
- Identifies dimensions and designs of experiments and creates test and learn frameworks.
- Interprets data to identify trends to go across future data sets.
- Creates continuous, online model learning along with iterative model enhancements.
- Develops 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.
Guides 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 & Scaling:
- Deploys models to production.
- Continuously logs and tracks model behavior once it is deployed against the defined metrics.
- Identifies model parameters which may need modifications depending on scale of deployment.
Code Development & Testing:
- Writes code to develop the required solution and application features by determining the appropriate programming
- language and leveraging business, technical, and data requirements.
- Creates test cases to review and validate the proposed solution design.
- Creates proofs of concept.
- Tests the code using the appropriate testing approach.
- Deploys software to production servers.
- Contributes code documentation, maintains playbooks, and provides timely progress updates.
Applied Business Acumen:
- Evaluates proposed business cases for projects and initiatives. Influences business stakeholder decision making.
- Translate 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.
- Challenge 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 learn more about industry practices.
Model Assessment & Validation:
- Identifies and reviews model evaluation metrics based on analytical requirements.
- Applies suitable techniques for model testing and tuning, to assess accuracy, fit, validity, and robustness.
- Ensures testing information is documented and maintained by the team.
- 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.
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 cost effectiveness; and participating in and supporting community outreach events.
- A proficiency in machine learning algorithms such as multi-class classifications, decision trees, support vector machines and deep learning
- Strong understanding of probability and statistical models (generative and descriptive models)
- The ability to run experiments scientifically and analyze results
- The ability to effectively communicate technical concepts and results to technical and business audiences in a comprehensive manner
- The ability to collaborate effectively across multiple teams and stakeholders, including analytics teams, development teams, product management and operations learning causal graphs
- Solid expertise with Operations Research, Artificial Intelligence (CSP, Search) Algorithms, System Design, Big Data Analysis (Map Reduce)
- Experience in designing and building highly scalable distributed ML models
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.
Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications.
Option 1: Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 5 years' experience in an analytics related field. Option 2: Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 3 years' experience in an analytics related field. Option 3: 7 years' experience in an analytics or related field
Outlined below are the optional preferred qualifications for this position. If none are listed, there are no preferred qualifications.
Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Publications or active peer reviewer in related journals or conference, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch)
Need convincing? Let's review Walmart's best features:
- 51%of reviewers say women and men are treated equally at Walmart.