Principal, Data Scientist

Position Summary...

What you'll do...

Code Development and Testing:

Requires knowledge of coding languages like SQL, Scala, Python 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.

Responsible for crafting simple, dependable data pipelines and automated reporting to surface metrics;

Test the code using the appropriate testing approach. Deploy code to production servers.

Contribute code documentation, maintain playbooks, and provide timely progress updates.

Problem Formulation: Requires knowledge of Analytics/big data analytics/automation techniques and methods;

Business requirements and insights:

Works with engineering to implement, document, validate, and monitor our logging and metrics; Identifying, translating, prioritizing, and informing important product questions with data; To analyze the business problem within one's discipline and questions assumptions to help the business identify the root cause.

Identify and recommend approach to resolve the business problem to create effective technology focused solutions.

Set relevant deliverables based on the established success criteria and define key metrics to measure progress and effectiveness of the solution. Quantify business impact.

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 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, referring to external sources as required.

Perform initial data quality checks on the extracted data. Review the deliverables of junior associates and provides guidance on data source and quality.

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 more functions or domains.

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.