Staff Data Scientist

What you'll do...

Position: Staff Data Scientist

Job Location: 221 River Street, Hoboken, NJ 07030

Duties: Translate and co-own business problems within one's discipline to data related or mathematical solutions. Identify appropriate methods and 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. 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. 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. Select appropriate modeling 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 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 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 modeling techniques to be used for complex problems with unstructured and multiple data sets. 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. 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. 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 conveys clear messages through business and stakeholder understanding. Customize communication style based on stakeholder under guidance and leverages rational arguments. Understand, articulate, and apply principles of the defined strategy to routine business problems that involve a single function.

Minimum education and experience required: Master’s degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, Engineering (Any), or related field and 2 years of experience in an analytics related field; OR Bachelor’s degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, Engineering (Any), or related field and 4 years of experience in an analytics related field.

Skills required: Experience developing and optimizing Machine Learning Models. Experience designing and implementing deep learning models for tasks using PyTorch and TensorFlow. Experience optimizing model performance through feature selection, hyperparameter tuning, and evaluation techniques. Experience conducting search and recommendation experiments, applying A/B testing, interleaving evaluations, and using causal inference methods to measure search quality improvements. Experience developing feature extraction techniques, including embedding representations, TF-IDF, word vectors, and contextual similarity features. Experience applying dimensionality reduction techniques (PCA, UMAP), interaction features, and categorical encoding methods to enhance model performance. Experience with Natural Language Processing (NLP) and Query Understanding, including implementing NLP techniques for query reformulation using spaCy, NLTK, and Hugging Face Transformers. Experience developing Named Entity Recognition (NER) models with spaCy and BERT and optimizing semantic search understanding using vector search libraries, including Faiss, Annoy, and Milvus. Experience analyzing user behavior, query logs, and search traffic patterns to derive insights for model improvement and business strategy. Experience deploying machine learning models on cloud platforms, including GCP and AWS. Experience using Docker and Kubernetes for scalable, efficient, and cost-effective inference pipelines. Experience processing large-scale search and recommendation data using PySpark and Hadoop. Experience developing scalable, production-ready machine learning and search system code in Python, Java, and SQL. Experience working with NoSQL databases (MongoDB) and relational databases (MySQL) to optimize query performance and data storage. Experience with Data Engineering and ETL Pipelines, including designing and maintaining data ingestion, transformation, and signal generation pipelines using Hive, SQL, and Kafka. Employer will accept any amount of experience with the required skills.

Salary Range: $139,506/year to $264,000/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. 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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Walmart and its subsidiaries are committed to maintaining a drug-free workplace and has a no tolerance policy regarding the use of illegal drugs and alcohol on the job. This policy applies to all employees and aims to create a safe and productive work environment.