AI Researcher & Data Scientist - Entry Level (Quantitative STEM)
פורסם אתמול · 0 מועמדים
- B.Sc. / M.Sc. / Ph.D. in quantitative fields (Mathematics, Statistics, Physics, Data Science, Engineering, or Economics)
- Deep mathematical foundation (Linear Algebra, Probability, Calculus)
- High level of English
חולץ מתיאור המשרה · מתעדכן אוטומטית
תיאור המשרה המלא
המשרה המקורית · נשמר לעיוןAbout the Job
Infinity Labs R&D is seeking high-achieving quantitative graduates to join a premier, specialized career path in Data and Artificial Intelligence.
Our business model is based on mutual success: we fully fund and invest in your advanced technical training because our growth depends entirely on your successful placement in key industry roles. You will master advanced research methodologies and scientific approaches to solve real-world industrial AI challenges.
Hands-on Experience You Will Gain:
• Model Development & Analytics: Supervised/Unsupervised learning, statistical modeling, data manipulation, and advanced validation techniques.
• Deep Learning & GenAI: Neural networks, Computer Vision, Natural Language Processing (NLP), and pre-trained model integration.
• Big Data Infrastructures: Managing and refining complex data at scale, constructing Data Pipelines, and building ML Pipelines.
Requirements:
• B.Sc. / M.Sc. / Ph.D. in quantitative fields (Mathematics, Statistics, Physics, Data Science, Engineering, or Economics).
• Strong academic indicators (GPA 80+ or Psychometric score 700+) – Major Advantage.
• Deep mathematical foundation (Linear Algebra, Probability, Calculus).
• High level of English.
• No prior professional experience in AI or Data Science required.
Participation in the program does not guarantee employment. Any future job offer is conditional upon successful completion of the training program, professional evaluation, and the availability of suitable positions.
שאלות על המשרה
- המשרה לא ציינה שכר. אנחנו מציגים שכר רק כשהמעסיק מפרסם אותו.
- B.Sc. / M.Sc. / Ph.D. in quantitative fields (Mathematics, Statistics, Physics, Data Science, Engineering, or Economics), Deep mathematical foundation (Linear Algebra, Probability, Calculus), High level of English