Senior Data Scientist

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What you'll do...

Position: Senior Data Scientist

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

Duties: Performs data visualization: visualization guidelines and best practices for complex data types; Multiple data visualization tools (Python, R libraries, GGplot, Matplotlib, Ploty, Tableau, PowerBI etc.); Advanced visualization techniques/ tools; Multiple story plots and structures (OABCDE); Communication & influencing technique; Emotional intelligence. Generates 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 conveys clear messages through business and stakeholder understanding. Customize communication style based on stakeholder under guidance and leverages rational arguments. Guide and mentor junior associates on story types, structures, and techniques based on context. Understanding Business Context: Requires knowledge of Industry and environmental factors; Common business vernacular; Business practices across two or more domains such as product, finance, marketing, sales, technology, business systems, and human resources and in-depth knowledge of related practices; Directly relevant business metrics and business areas. To 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 aligns to overall business strategy and develops 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. Tech. Problem Formulation: Requires knowledge of Analytics/big data analytics / automation techniques and methods; Business understanding; Precedence and use cases; Business requirements and insights. To translate/ co-own 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 gives examples to demonstrate how the method would solve the business problem. Analytical Modeling: Requires knowledge of feature relevance and selection; Exploratory data analysis methods and techniques; Advanced statistical methods and best-practice advanced modelling techniques (e.g., graphical models, Bayesian inference, basic level of NLP, Vision, neural networks, SVM, Random Forest etc.); Multivariate calculus; Statistical models behind standard ML models; Advanced excel techniques and Programming languages like R/Python; Basic classical optimization techniques (e.g., Newton-Rapson methods, Gradient descent); Numerical methods of optimization (e.g. Linear Programming, Integer Programming, Quadratic Programming, etc.) To select the analytical modeling technique most suitable for the structured, complex data and develops custom analytical models. Conduct exploratory data analysis activities (for example, basic statistical analysis, hypothesis testing, statistical inferences) on available data. Define and finalize features based on model responses and introduces 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. Mentor and guide junior associates on basic modeling and analytics techniques to solve complex problems.

Minimum education and experience required: Master's degree or the equivalent in Computer Science, Statistics, or related field plus 1 year of experience in analytics or a related field; OR Bachelor’s degree or the equivalent in Computer Science, Statistics, or related field plus 3 years of experience in analytics or a related field.

Skills required: Must have experience with: Architecting and implementing deepAR, Prophet time series deep learning forecasting models using Pytorch and Python; Designing and implementing data transit automation pipelines using Airflow and GCP; Developing and deploying scalable microservices using Docker and Kubeflow; Building and maintaining GCP and Databricks relational databases using SQL and Pyspark; Implementing Continuous Integration/Continuous Deployment (CI/CD) pipelines using Git; Leveraging auto machine learning frameworks based on Kubeflow in GCP; Conducting ad hoc analysis and back testing using Python and Excel to validate the stability and improve the accuracy of forecasting services. Employer will accept any amount of experience with the required skills.

Pay Rate...