Principal Data Scientist

Principal Data Scientist

02 Nov 2021
California, Sunnyvale, 94086 Sunnyvale USA

Principal Data Scientist

job summary:

Company started with the simple idea of selling more for less. Over

the last 50 years it has grown into the largest retailer in the world,

with more than 265 million customers each week across 11,000

stores worldwide. Sustaining that growth, size, and corporate value creates many

exciting opportunities and challenges in all areas of retail commerce.



location: Sunnyvale, California

job type: Permanent

salary: $140,000 - 150,000 per year

work hours: 8am to 4pm

education: Doctorate



responsibilities:

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.




Data Strategy: 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.




Problem Formulation: 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.




Analytical Modeling: 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.




Data Visualization: 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.




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.






qualifications:


  • Experience level: Experienced
  • Minimum 5 years of experience
  • Education: Doctorate (required)


skills:
  • scala
  • Google Cloud Platform
  • tensorflow
  • torch



Equal Opportunity Employer: Race, Color, Religion, Sex, Sexual Orientation, Gender Identity, National Origin, Age, Genetic Information, Disability, Protected Veteran Status, or any other legally protected group status.



Qualified applicants in San Francisco with criminal histories will be considered for employment in accordance with the San Francisco Fair Chance Ordinance.



We will consider for employment all qualified Applicants, including those with criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the City of Los Angeles' Fair Chance Initiative for Hiring Ordinance.

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Job Details

  • ID
    JC5437135
  • State
  • City
  • Job type
    Permanent
  • Salary
    USD $140k - 150k per year 140k - 150k per year
  • Hiring Company
    Randstad Corporate Services
  • Date
    2020-11-02
  • Deadline
    2021-01-01
  • Category

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