Data Scientist III
| Company | Walmart |
|---|---|
| Location | Bentonville, AR, USA |
| Salary | $Not Provided – $Not Provided |
| Type | Full-Time |
| Degrees | Bachelor’s, Master’s |
| Experience Level | Mid Level, Senior |
Requirements
- Master’s degree or the equivalent in Computer Science, Information Technology, Engineering, or related field; OR Bachelor’s degree or the equivalent in Computer Science, Information Technology, Engineering, or related field plus 2 years of experience in data science or a related field
- Experience with analytical modeling: appropriate feature selection, EDA methods, and techniques
- Advanced Excel function and pivot tables for analyzing and visualizing the data
- Python, R programming language coding for data exploration, visualization, and pipeline development
- SQL for accessing database and exploration
- Business context and Tech problem formulation
- Root cause analysis
- Exploratory data analysis to understand how the feature behave before ML modelling
- Data visualization and creating dashboards using Tableau
- Cost savings/avoidance analysis
- Machine learning: regression, classification models, regularization, ensemble learnings, clustering
- Six Sigma: measurement system analysis (Gauge R&R), control charts, hypothesis testing and ANOVA analysis, sampling techniques, process improvement and factorial design experiments
Responsibilities
- 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
- 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
- Participating in the continuous improvement of data science and analytics by developing replicable solutions
- Building and maintaining a library of reusable algorithms for future use
- Ensuring developed code is documented
- 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
- Presenting data insights and recommendations to key stakeholders
Preferred Qualifications
-
No preferred qualifications provided.