Staff Data Scientist

Walmart•Bentonville, AR

1d•Onsite

About The Position

This Staff Data Scientist position involves a range of responsibilities from data source identification and strategy to advanced analytical modeling, model deployment, and code development. The role requires applying principles of data strategy to routine business problems, assessing and validating models for accuracy and robustness, and generating appropriate data visualizations. It also involves understanding business context to provide recommendations, translating business problems into data-related or mathematical solutions, and developing and deploying machine learning algorithms while continuously tracking their behavior.

Requirements

Master’s degree or the equivalent in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field plus 2 years of experience in analytics or related experience; OR Bachelor’s degree or the equivalent in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field plus 4 years of experience in analytics or related experience; OR 6 years of experience in analytics or related experience.
Coding in object-oriented programming language Python to build models and applications.
Developing Supervised and Unsupervised Learning algorithms using Scikit-learn, Matplotlib, Numpy, Pandas.
Data manipulation, data processing, exploratory data analysis (EDA) using Pandas, Seaborn, and SAS.
Building dashboard for post-processing of simulation results in Python, PowerBI or Tableau.
Sourcing data using SQL in different platforms such as BigQuery or relational database.
Statistics and probability solutioning suing Scipy.stats and Statsmodels in Python.
Database design to store the data generated from internally built platform using SQLite.
Developing front-end solution using CSS, HTML, and Plotly.
Utilizing ensemble techniques such as boosting, bagging, stacking to get strong and accurate models.
Model validation and evaluation using metrics and models in Scikit-learn framework.
Developing various AI/ML models and algorithms in the back end using Scikit-learn, Tensorflow, PyTorch and Keras.
Building API to web-scrape data and pre-process layout / asset data.
Performing analytic modeling, predictive modeling, regression analysis, hypothesis testing, ANOVA, and t-test etc. using Scikit-learn, Scipy.stats, and Statsmodels to get business insights.
Building Agent-based model or simulation and performing Monte Calo simulations.
Solving optimization problems using Dynamic Programing or Linear Programing by utilizing the statistical programing language (Python / R / Matlab).

Responsibilities

Support the understanding of 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.
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 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.
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.
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.
Select appropriate modelling techniques for complex problems with large scale, multiple structured and unstructured data sets.
Select and develop variables and features iteratively based on model responses in collaboration with the business.
Conducts exploratory data analysis activities (for example, basic statistical analysis, hypothesis testing, statistical inferences) on available data.
Identify dimensions and designs of experiments and create test and learn frameworks.
Interpret data to identify trends to go across future data sets.
Create continuous, online model learning along with iterative model enhancements.
Develop newer techniques (for example, advanced machine learning algorithms, auto ML) by leveraging the latest trends in machine learning, artificial intelligence to train algorithms to apply models to new data sets.
Guide the team on feature engineering, experimentation, and advanced modelling techniques to be used for complex problems with unstructured and multiple data sets (for example, streaming data, raw text data).
Deploy models to production.
Continuously log and track model behavior once it is deployed against the defined metrics.
Identify model parameters which may need modifications depending on scale of deployment.
Write code to develop the required solution and application features by determining the appropriate programming language and leveraging business, technical, and data requirements.
Create test cases to review and validate the proposed solution design.
Create proofs of concept.
Test the code using the appropriate testing approach.
Deploy software to production servers.
Contribute code documentation, maintain playbooks, and provide timely progress updates.