at Wal-Mart Associates, Inc. in Bentonville, Arkansas, United States
Duties: Supports the development of business cases and recommendations. Owns delivery of project activity and tasks assigned by others. Supports process updates and changes. Solves business issues. Understands the appropriate data set required to develop simple models by developing initial drafts. Supports the identification of the most suitable source for data. Maintains awareness of data quality. Understands, articulates, and applies principles of the defined strategy to routine business problems that involve a single function. Selects the analytical modeling technique most suitable for the structured, complex data and develops custom analytical models. Conducts exploratory data analysis activities (for example, basic statistical analysis, hypothesis testing, statistical inferences) on available data. Defines and finalizes features based on model responses and introduces new or revised features to enhance the analysis and outcomes. Identifies the dimensions of the experiment, finalizes the design, tests hypotheses, and conducts the experiment. Perform trend and cluster analysis on data to answer practical business problems and provide recommendations and key insights to the business. Mentors and guides junior associates on basic modeling and analytics techniques to solve complex problems. Supports efforts to ensure that analytical models and techniques used can be deployed into production. Supports evaluation of the analytical model. Supports the scalability and sustainability of analytical models. Writes code to develop the required solution and application features by using the recommended programming language and leveraging business, technical, and data requirements. Test the code using the recommended testing approach. Translates business problems within one's discipline to data related or mathematical solutions. Identifies what methods (for example, analytics, big data analytics, automation) would provide a solution for the problem. Shares use cases and gives examples to demonstrate how the method would solve the business problem. Supports model fit testing and statistical inferences to evaluate performance. Assesses the impact of variables and features on model performance. Generates appropriate graphical representations of data and model outcomes under guidance. Supports the understanding of customer requirements and designs data representations for simple data sets. Presents to and influences the team using the appropriate frameworks and conveys messages through basic business understanding. 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.
Minimum education and experience required: Bachelor’s degree or the equivalent in Statistics, Analytics, Computer Science, Engineering, or related field plus 2 years of experience in analytics or a related field; OR Master’s degree or the equivalent in Statistics, Analytics, Computer Science, Engineering, or related field; OR 4 years of experience in analytics or a related field.
Skills Required: Must have experience with: SQL queries to perform data extraction from Teradata and Hadoop databases; Analyzing the data and providing insights from the data by performing various analytical tasks and exploratory and Descriptive Statistics of the data using R and Python; Data transformations including creating new variables, aggregating, decomposing variables and missing data treatment using imputation techniques like MAR, MCAR using SQL, Python and R; Feature Extraction using Principle Component Analysis to be used in the Tree based models such as Random Forest, XgBoost using Python; Building statistical models and Machine Learning models such as Linear Regression, Multi Linear Regression, Ridge Regression, XG Boost using Python and R; Building Time Series forecasting models using FBProphet and ARIMA; Building unsupervised machine learning models involving Text Mining using Python; Predictive modeling using various ML algorithms in Python, R; Building Machine Learning algorithms using analytical tools such as SAS, R, or Python; Presenting the insights to the business to solve the business problems; and Visualization of the data using Tableau/Excel to show the key performance indicators for the business along with the key insights. Employer will accept any amount of graduate coursework, graduate research experience or professional experience with the required skills.
To apply for this position: Send your resume to email@example.com and reference the following Job ID number: R-801702