Data Scientist III

Walmart•San Bruno, CA

1d•$133,952 - $234,000•Onsite

About The Position

This position is for a Data Scientist III located at 850 Cherry Avenue, San Bruno, CA 94066. The role involves demonstrating expertise in data science, applying it to develop and improve action plans, and providing expert advice. It requires building partnerships with stakeholders, identifying business needs, and implementing solutions. The Data Scientist III will model compliance with company policies and support the company's mission and values. This role also entails leading small and participating in large data analytics project teams, serving as a technical lead, defining project goals, developing contingency plans, determining modeling strategies, directing data analysis, gathering data, developing reports, ensuring data accuracy, and communicating insights to stakeholders. Additionally, the position involves presenting data insights and recommendations, developing replicable solutions for continuous improvement, building a library of reusable algorithms, documenting code, and mentoring analysts. The Data Scientist III will develop analytical models using internal and external data sources, evaluate data usability, synthesize data into large datasets, develop statistical models and computational algorithms, utilize the analytics project lifecycle for predictive modeling, code and maintain analytical software tools, identify trends and patterns, train statistical models, and present findings to stakeholders.

Requirements

Master’s degree or equivalent in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or related field; OR Bachelor’s degree or equivalent in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or related field and 2 years of experience in an analytics or related field.
Experience with conducting extensive data analysis using object-oriented programming languages like Python.
Experience with performing data manipulation using SQL.
Experience working on cloud-based data storage like Google Cloud Platform and Hive to save and manipulate data.
Experience working with version control systems like Git and GitHub.
Experience conducting inferential statistical analysis to test hypotheses and deriving estimates to give recommendations.
Experience using Tableau or Looker to create dashboard and conduct visualization analysis.
Experience using machine learning techniques such as regression, tree-based ensemble methods, clustering, dimensionality reduction, neural networks and models to predict.
Experience using cross-validation, ROC/AUC, and precision-recall rate to evaluate model performance.
Employer will accept any amount of graduate coursework, graduate research experience or professional experience with the required skills.

Responsibilities

Demonstrates up-to-date expertise and applies this to the development, execution, and improvement of action plans by providing expert advice and guidance to others in the application of information and best practices; supporting and aligning efforts to meet customer and business needs; and building commitment for perspectives and rationales.
Provides and supports the implementation of business solutions by building relationships and partnerships with key stakeholders; identifying business needs; determining and carrying out necessary processes and practices; monitoring progress and results; recognizing and capitalizing on improvement opportunities; and adapting to competing demands, organizational changes, and new responsibilities.
Models compliance with company policies and procedures and supports company mission, values, and standards of ethics and integrity by incorporating these into the development and implementation of business plans; using the Open Door Policy; and demonstrating and assisting others with how to apply these in executing business processes and practices.
Leads small and participates in large data analytics project teams by serving as a technical lead for analytics projects; working with project teams and business partners to determine project goals; developing contingency plans for data analysis; determining modeling based on business needs; directing the analysis of data; gathering data and developing reports as needed; utilizing business knowledge to ensure data supports project goals; analyzing data based on identified variables; reviewing data results to ensure accuracy; and communicating results and insights to the project team and business partners.
Presents data insights and recommendations to key stakeholders by developing insights based on data analysis; applying analytical results to project goals; identifying trends and key insights; translating results into business actions; and presenting insights and recommendations to key stakeholders.
Participates in the continuous improvement of data science and analytics by developing replicable solutions (for example, codified data products, project documentation, process flowcharts) to ensure solutions are leveraged for future projects; building and maintaining a library of reusable algorithms for future use; ensuring developed code is documented; and coaching and mentoring analysts across the division and project teams.
Develops analytical models to drive analytics insights by gathering data from internal and external sources; evaluating data usability based on project goals; synthesizing data into large datasets to support project goals; developing statistical models and computational algorithms to analyze data; utilizing the analytics project lifecycle process to drive predictive modeling; coding, testing, and maintaining analytical software tools; identifying trends, patterns and discrepancies in data; training statistical models for replication for future projects; and presenting data insights and recommendations to key stakeholders.