Data Scientist (LLM/NLP)

ITAC Solutions
Birmingham
2 months ago
Applications closed

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Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Step into a high-impact role where your advanced data science expertise directly shapes data-driven decisions across an enterprise environment. In this position, you’ll design intelligent solutions leveraging NLP, LLMs, and machine learning to solve complex business challenges. If you enjoy building meaningful AI applications from the ground up, this opportunity puts you at the center of innovation for our client.


C2C is not an option with this job opening and all applicants should be able work for any US Employer without sponsorship. Sponsorship is not provided and this person will not need to require sponsorship in the future.


Benefits & Extras

  • Three healthcare plan options with tiers available for you or your whole family.
  • Two dental plan options to ensure the right level of coverage.
  • A vision plan through a highly trusted national carrier.
  • Upon meeting eligibility requirements, the opportunity to participate in ITAC’s retirement plan.
  • Weekly pay via direct deposit or pay card.

Compensation

  • Conversion Salary Range: $100,000 – $125,000
  • Contract rate: $50/hr

What You’ll Be Doing

  • Designing and implementing advanced analytics solutions.
  • Building NLP and LLM-based applications from concept to deployment.
  • Mining and analyzing large structured and unstructured datasets.
  • Collaborating with business stakeholders to define goals and success criteria.
  • Developing, evaluating, and deploying predictive models.
  • Communicating insights to technical and non-technical audiences.
  • Monitoring and maintaining model performance post-deployment.

What You’ll Need to be Considered

  • 2+ years of relevant experience
  • Ability to work with unstructured data at scale.
  • Experience building and deploying LLM solutions.
  • Degree in Data Science, Statistics, Computer Science, or related field.
  • Familiarity with deep learning frameworks.
  • Knowledge of cloud platforms (AWS, GCP, or Azure).


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