Wal-Mart Associates, Inc.
Senior Data Scientist
Wal-Mart Associates, Inc., Hoboken, New Jersey, us, 07030
```htmlPosition: Senior Data ScientistJob Location:
221 River Street, Hoboken, NJ 07030
Duties:
Stay up-to-date with the latest machine learning and deep learning algorithms that power Personalization on Walmart’s website and stores.
Stay proficient on big data technologies such as Hive and Map-Reduce framework, build algorithms to handle massive amounts of data generated on the web, and make data-driven inferences at scale.
Work with the latest data science and software engineering technologies being used within the Personalization team such as but not limited to Java, Hive, Map-Reduce framework, Python, Bash scripting, Couchbase, and Machine Learning packages such as Scikit-Learn and Numpy.
Collaborate with team members in Personalization data engineering, modeling team, and web service to deliver key projects.
Adhere to best practices for software development such as coding styles, code reviews from peers, continuous build with Jenkins, and integrated deployment with OneOps.
Design different components in Personalization backend systems, from data collection to enabling machines to make data-driven decisions at scale, thus building highly scalable and relevant solutions to drive key business projects.
Develop new machine learning and artificial intelligence techniques to achieve business goals.
Clearly articulate work and document, track, and present accomplished tasks through tools such as Jira, Github, and Confluence.
Analyze customer and catalog data to build state-of-the-art personalized item recommendation models.
Develop, deploy, A/B test, and launch machine learning models in production and measure the impact on business metrics.
Minimum education and experience required:
Master’s degree or equivalent in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 1 year of experience in an analytics or related field;
OR
Bachelor’s degree or equivalent in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 3 years of experience in an analytics or related field.
Skills required:
Experience processing and analyzing big data using Pyspark, Hive, and Map-Reduce framework.
Experience implementing and building production pipelines using Python.
Experience building Classification and Deep Learning models using Pyspark, Pytorch, and Tensorflow.
Experience designing and testing new recommendation algorithms using collaborative filtering, content-based methods, and context-sensitive approaches.
Experience automating pipelines using Apache Airflow for scheduling.
Experience working with NLP models using techniques including topic modeling and named-entity recognition using LDA.
Experience with long-term forecasting using LSTM or Causal Inference model.
Experience with Hypothesis Testing, Probability Distribution, and A/B Testing.
Experience designing and implementing REST API using Flask.
Experience using Autoencoders for new data generation, image compression, and removing noise from images.
Experience processing images using OpenCV or PIL.
Experience with multiprocessing pipelines using Dask.
Experience working with one of the following Deep Learning Image models: AlexNet or InceptionV3.
Experience using one of the following Deep Learning techniques for personalization and recommendations: DLRM, DRL, or Transformer.
Experience using Unified Pairwise and Pointwise ranking algorithms for recommendation and ranking.
Experience working with public cloud-based technology Google Cloud Platform.
Experience using JIRA, Bash, and Github.
Employer will accept any amount of experience with the required skills.
```#J-18808-Ljbffr
221 River Street, Hoboken, NJ 07030
Duties:
Stay up-to-date with the latest machine learning and deep learning algorithms that power Personalization on Walmart’s website and stores.
Stay proficient on big data technologies such as Hive and Map-Reduce framework, build algorithms to handle massive amounts of data generated on the web, and make data-driven inferences at scale.
Work with the latest data science and software engineering technologies being used within the Personalization team such as but not limited to Java, Hive, Map-Reduce framework, Python, Bash scripting, Couchbase, and Machine Learning packages such as Scikit-Learn and Numpy.
Collaborate with team members in Personalization data engineering, modeling team, and web service to deliver key projects.
Adhere to best practices for software development such as coding styles, code reviews from peers, continuous build with Jenkins, and integrated deployment with OneOps.
Design different components in Personalization backend systems, from data collection to enabling machines to make data-driven decisions at scale, thus building highly scalable and relevant solutions to drive key business projects.
Develop new machine learning and artificial intelligence techniques to achieve business goals.
Clearly articulate work and document, track, and present accomplished tasks through tools such as Jira, Github, and Confluence.
Analyze customer and catalog data to build state-of-the-art personalized item recommendation models.
Develop, deploy, A/B test, and launch machine learning models in production and measure the impact on business metrics.
Minimum education and experience required:
Master’s degree or equivalent in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 1 year of experience in an analytics or related field;
OR
Bachelor’s degree or equivalent in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 3 years of experience in an analytics or related field.
Skills required:
Experience processing and analyzing big data using Pyspark, Hive, and Map-Reduce framework.
Experience implementing and building production pipelines using Python.
Experience building Classification and Deep Learning models using Pyspark, Pytorch, and Tensorflow.
Experience designing and testing new recommendation algorithms using collaborative filtering, content-based methods, and context-sensitive approaches.
Experience automating pipelines using Apache Airflow for scheduling.
Experience working with NLP models using techniques including topic modeling and named-entity recognition using LDA.
Experience with long-term forecasting using LSTM or Causal Inference model.
Experience with Hypothesis Testing, Probability Distribution, and A/B Testing.
Experience designing and implementing REST API using Flask.
Experience using Autoencoders for new data generation, image compression, and removing noise from images.
Experience processing images using OpenCV or PIL.
Experience with multiprocessing pipelines using Dask.
Experience working with one of the following Deep Learning Image models: AlexNet or InceptionV3.
Experience using one of the following Deep Learning techniques for personalization and recommendations: DLRM, DRL, or Transformer.
Experience using Unified Pairwise and Pointwise ranking algorithms for recommendation and ranking.
Experience working with public cloud-based technology Google Cloud Platform.
Experience using JIRA, Bash, and Github.
Employer will accept any amount of experience with the required skills.
```#J-18808-Ljbffr