Senior Data Scientist
4 days ago
Position: Senior Data Scientist
Job Location: 640 W. California Avenue, Sunnyvale, CA 94086
Duties: Support the priority order of requirements and service level agreements. Help identify the most suitable source for data that is fit for purpose. Perform initial data quality checks on extracted data. Understand, articulate, and apply principles of the defined strategy to routine business problems that involve a single function. Support efforts to ensure that analytical models and techniques used can be deployed into production. Support evaluation of the analytical model and the scalability and sustainability of analytical models. Write 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. Identify the model evaluation metrics. Apply best practice techniques for model testing and tuning to assess accuracy, fit, validity, and robustness for multi-stage models and model ensembles. Generate appropriate graphical representations of data and model outcomes. Understand customer requirements to design appropriate data representation for multiple data sets. Work with User Experience designers and User Interface engineers as required to build front end applications. Present to and influence the team and business audience using the appropriate data visualization frameworks and convey clear messages through business and stakeholder understanding. Customize communication style based on stakeholder under guidance and leverage rational arguments. Guide and mentor junior associates on story types, structures, and techniques based on context. Provide recommendations to business stakeholders to solve complex business issues. Develop business cases for projects with a projected return on investment or cost savings. Translate business requirements into projects, activities, and tasks and align to overall business strategy and develop domain specific artifact. Serve as an interpreter and conduit to connect business needs with tangible solutions and results. Identify and recommend relevant business insights pertaining to their area of work. Translate business problems within one's discipline to data related or mathematical solutions. Identify appropriate methods/tools to be leveraged to provide a solution for the problem. Share use cases and give examples to demonstrate how the method would solve the business problem. Select the analytical modeling technique most suitable for the structured, complex data and develop custom analytical models. Conduct exploratory data analysis activities (for example, basic statistical analysis, hypothesis testing, and statistical inferences) on available data. Define and finalize features based on model responses and introduce new or revised features to enhance the analysis and outcomes. Identify the dimensions of the experiment, finalize the design, test hypotheses, and conduct the experiment. Perform trend and cluster analysis on data to answer practical business problems and provide recommendations and key insights to the business.
Minimum education and experience required: Master’s degree or equivalent in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, Engineering (any), or related field and 1 year of experience in an analytics related field; OR Bachelor’s degree or equivalent in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, Engineering (any), or related field and 3 years of experience in an analytics related field.
Skills required: Experience with database technologies and distributed datastores including SQL and NoSQL. Experience with coding languages including SQL, Java, C++, and Python. Experience with Machine Learning model training, testing, tuning, and validation techniques including Chi square, ROC curve, and root mean square error. Experience with data visualization tools including Python, Matplotlib, and Ploty. Experience with feature relevance and selection and exploratory data analysis methods and techniques. Experience with advanced statistical methods and best-practice advanced modelling techniques including graphical models, Bayesian inference, NLP, Vision, neural networks, SVM, and Random Forest. Experience with Multivariate calculus and statistical models behind standard ML models. Experience with analytics, big data analytics, and automation techniques and methods. Experience with classical optimization techniques including Newton-Rapson methods and Gradient descent. Experience with numerical methods of optimization including Linear Programming, Integer Programming, and Quadratic Programming. Experience with business value and relevance of data and data enabled insights and decisions. Employer will accept any amount of experience with the required skills.
Salary Range: $138,911/year to $234,000/year. Additional compensation includes annual or quarterly performance incentives. Additional compensation for certain positions may also include: Regional Pay Zone (RPZ) (based on location) and Stock equity incentives.
Benefits: At Walmart, we offer competitive pay as well as performance-based incentive awards and other great benefits for a happier mind, body, and wallet. Health benefits include medical, vision and dental coverage. Our financial benefits include 401(k), stock purchase and company-paid life insurance. Paid time off benefits include PTO (including sick leave), parental leave, family care leave, bereavement, jury duty and voting. Other benefits include short-term and long-term disability, education assistance with 100% company paid college degrees, company discounts, military service pay, adoption expense reimbursement, and more.
Eligibility requirements apply to some benefits and may depend on your job classification and length of employment. Benefits are subject to change and may be subject to a specific plan or program terms. For information about benefits and eligibility, see One.Walmart.com.
Wal-Mart is an Equal Opportunity Employer.
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