What you'll do...

Position: Data Scientist III

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

Duties: Applied Business Acumen: 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. Data Source Identification: Understand 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. Data Strategy: Understands, articulates, and applies principles of the defined strategy to routine business problems that involve a single function. Analytical Modeling: 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. Model Deployment & Scaling: 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. Code Development & Testing: 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. Problem Formulation: 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. Model Assessment & Validation: Supports model fit testing and statistical inferences to evaluate performance. Assesses the impact of variables and features on model performance. Data Visualization: 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 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 analytics or related experience.

Skills required: Must have experience with: Understanding structural, algorithmic and computational aspects of linear programming (simplex method, ellipsoid algorithm, interior point algorithm, decomposition techniques etc.); Understanding and writing methods to solve non-linear programming (convex set, covex optimization, algorithm for unconstrained and constrained optimization such as Newton's method, Logarithmic barrier function, primal - dual interior point method etc.); Applying theory and methods of dynamic programming to applications including deterministic DP problems and stochastic DP problems, understand Markov decision process and reinforcement learning process; Master algorithms to solve integer programming such as cutting plane approaches, branch-and-bound methods, Lagrangian relaxation, Bender's decomposition etc.); Graph theory and its application in supply chain filed (assignment problem, vehicle routing problem etc.); Understanding NP problem and write algorithm to find an approximation solution includes meta-heuristic method such as genetic algorithm, simulated annealing method etc. and approximation method such as greedy algorithm, local search method etc.; Building mathematical model and perform numerical simulation (finite-difference method, Monte Carlo method etc.); Developing optimization model based on requirement and obtain solving using common solves such as Gurobi, CPLEX, OR-Tools, etc.; Strong foundation in statistics includes design correlation and regression analysis, perform hypothesis testing, calculate probability, understand stochastic processes and familiar with most statistical models; Common machine learning model and its application includes supervised learning algorithms such as linear regression, k-nearest neightbors, support vector machines, etc. and unsupervised learning algorithms such as K-means, principal component analysis etc.; Deep learning including convolutional neural networks, recurrent neural network, natural language processing, generative adversarial networks etc.; Coding in an object-oriented programming language (Python, MATLAB, C++); Common statistical and machine learning package (Numpy, Pandas, Matplotlib, Scikit-learn, SciPy); Common deep learning package (Tensorflow, NLTK, PyTorch); and Machine learning and operation research algorithms to be able to implement models to solve business problem. Employer will accept any amount of graduate coursework, graduate research experience or experience with the required skills.

Wal-Mart is an Equal Opportunity Employer.

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