Senior Data Scientist

2 weeks ago


Canada Intellias Full time

Dive deep into Digital For 20 years Intellias has been developing top-tier digital solutions for the world's leading companies, keeping them in line with the latest technology trends. Join in and provide innovations for the future

Project Overview:

We are seeking a Data Scientist with expertise in machine learning, large language models (LLMs), and AI-driven solutions. The ideal candidate will have a strong foundation in traditional statistical models and machine learning techniques, coupled with hands-on experience in LLM development and prompt engineering. This role requires technical proficiency in Python, Docker, and GitLab CI/CD, with a preference for experience in FastAPI. We value individuals who take initiative, demonstrate great work ethics, and focus on the overall success of projects.

Requirements:

  • Strong understanding of machine learning models, statistical analysis, and data science principles.
  • GCP proficiency is a must
  • Hands-on experience with LLMs, prompt engineering, and AI model optimization.
  • Proficiency in Python, Docker, and GitLab CI/CD for data science workflows.
  • (Preferred) Experience with FastAPI for API development and deployment.
  • Strong problem-solving skills and a proactive approach to project execution.
  • Excellent teamwork, communication, and initiative in delivering impactful solutions.
  • Ability to work EST hours

Responsibilities:

  • Develop, train, and optimize traditional machine learning models for data analysis and predictive insights.
  • Apply expertise in LLMs and prompt engineering to create and refine AI-driven applications.
  • Utilize Python, Docker, and GitLab CI/CD for model development, automation, and deployment.
  • (Preferred) Implement FastAPI for building scalable APIs and integrating machine learning models into production environments.
  • Collaborate with cross-functional teams to drive AI-powered innovations and ensure project success.
  • Maintain a high standard of coding practices, version control, and model performance evaluation.

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