Data Scientist

What you'll do...

Position: Data Scientist

Job Location: 702 SW 8th Street, Bentonville, AR 72716

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: Master’s degree or the equivalent in Statistics, Analytics or related field; OR Bachelor’s degree or the equivalent in Statistics, Analytics or a related field plus 2 years of experience in analytics or a related field.

Skills Required: Must have experience with: retrieving data from database servers IBM DB2, Microsoft SQL Server, Oracle and MYSQL; data visualization using Python packages (Matplotlib, Seaborn, Plotly, Ggplot and Geoplotlib) and R packages (ggplot2, shiny, Lattice, highcharter, RColorBrewer, Plotly, plot3D and sunburstR); Python (NumPy, SciPy, Pandas, SciKit-Learn, BeautifulSoup and PySpark), R (dplyr, tidyr, knitr, data.table and tidyverse), SQL and T-SQL to manipulate data; Statistics/Probability (Various probability distributions, Hypothesis testing, Bayesian concepts, Experimental design, and Sampling Methods); supervised machine learning models including building and deployment (Linear Regression, Logistical Regression, KNN, SVM, Random Forest, XGBoost, Naïve Bayes and Elastic Net) to solve business problems; unsupervised machine learning models building and deployment (K-means, Gaussian Mixture Model, Principal Component Analysis, Singular Value Decomposition, and Independent Component Analysis) to solve business problems; deep learning models building and deployment (CNN, LSTM, RNN and NLP); time series models (ARIMA, SARIMA, Simple Exponential Smoothing, Holt Winter’s Exponential Smoothing) for forecasting; causal inferencing, multi-variate testing & design, A/B testing & design, descriptive analytics, and regression analysis; Cloud computing services like GCP and Azure; open-source frameworks like TensorFlow, Pytorch and Keras; programming languages (Python, R, SQL, C++ and Java Script); Version Control (Git); code testing including unit test, integration test, functional test, and end-to-end test, and test library, pytest and unittest; end-to-end data science processes including identifying and defining the problem, building data pipelines, and deploying and validating a solution. Employer will accept any amount of experience with the required skills.

#LI-DNP #LI-DNI

Wal-Mart is an Equal Opportunity Employer.