Data Scientist/ AI Engineer @ SquareOne in SquareOne

Data Scientist/ AI Engineer Are you passionate about leveraging data to drive innovation and solve complex business challenges? Join our client’s dynamic team and embark on an exciting journey of delivering cutting-edge data solutions to our diverse range of clients worldwide. Requirements: Bachelor's or Master's degree in Mathematics, Computer Science, Physics, Operational Research, or related field. Proven track record of successfully executing data science solutions in commercial settings. Proficiency in data analysis tools and technologies such as SQL, Python, and PySpark. Knowledge of tools and programming languages for analyzing large datasets (e.g., Spark, Data Bricks, Pig). Familiarity with genAI, LLMs (e.g., GPT, Mistral, LLama2, Phi), orchestrators, vector storages, and inference platforms. Good understanding of SQL and NoSQL databases. Eagerness to learn new tools and software solutions. Excellent command of English with strong interpersonal and communication skills. Focus on teamwork and leadership abilities. Willingness to occasionally travel to meet client needs. Additional Requirements (nice to have): Experience working in a global/multinational team environment. Hands-on experience with cloud services such as Azure, AWS, or GCP. Up-to-date knowledge of current trends and advancements in the data science field. Previous experience in deep learning, computer vision, and/or geo analytics is a plus. Familiarity with agile methodologies like Scrum or Kanban. Interest in behavioral economics and/or data science. Github profile. Data Scientist/ AI Engineer Are you passionate about leveraging data to drive innovation and solve complex business challenges? Join our client’s dynamic team and embark on an exciting journey of delivering cutting-edge data solutions to our diverse range of clients worldwide. ,[Utilize your expertise in quantitative business analysis, data mining, and AI to uncover valuable insights from data., Deploy machine learning models into production environments in collaboration with data engineers., Ensure seamless integration of machine learning models with data pipelines., Work closely with product teams to design and implement data-driven solutions., Collaborate with Applications and Products development teams to operationalize machine learning models in final products.] Requirements: AI, SQL, Python, PySpark, Spark, NoSQL, LLM, Cloud, Deep learning, Azure, AWS, GCP, Kanban, GitHub