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Data Scientist

3 months ago

Greenville, United States Vertisystem Full time

Qualifications:

Provides machine learning production solutions to support the deployment and operations of ML Models in a cloud environment. Collaborates with product owners, data scientists, business analysts and data engineers to design, build and enhance platforms and services in an AI cloud-based ecosystem. Ability to communicate with the business and formulate problems on the spot. Explore a data set and be able to formulate a problem and evaluate it. Should have an understanding of the DS problem life cycle. Should have worked on actual Machine Learning use cases. Interpret Machine learning scorers. Consult with business users to evaluate their business problems and datasets for potential machine learning use cases.


Requirements:

  • Strong understanding of business problems and ability to translate them into ML solutions.
  • Experience deploying ML models into production.
  • Research experience.
  • 80% focus on ML and business-related tasks.
  • Manufacturing experience is a significant advantage.
  • Ability to work with business teams and integrate ML solutions into ongoing programs.
  • Expertise in Generative AI, use cases, refining existing applications, and developing new templates.
  • Proficiency in Python and ML techniques is essential.
  • Experience in NLP is a plus.
  • Availability to work 2 days a week.


Key Responsibilities:

  • Understand business problems and develop ML solutions.
  • Deploy and manage models in production.
  • Collaborate with business teams to ensure ML solutions are effectively integrated.
  • Focus on generative AI applications and refining existing systems.


A day in the life includes:

  • Working with large data sets and prepping the data for consumption
  • Assessing the effectiveness and accuracy of data sources
  • Working with business users to obtain more insight into data sources. Asking the right questions to understand how the data can be used.
  • Evaluating the results of machine learning algorithms – determining their explainability
  • Determining the feasibility of a use case given the business problem and the available data.
  • Monitoring and analyzing model performance
  • Performing prompt engineering tasks with specific use cases.


Education:

  • Bachelor degree in computer science, mathematics/statistics or related field.
  • Advanced degree (Masters or PhD) in computer science, mathematics/statistics or a related field (preferred).