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Data Scientist

Salary undisclosed

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Technical Skills:

AI and Machine Learning:

  • Strong proficiency in developing and deploying AI/ML models, with expertise in one or more areas: Machine Learning, Natural Language Processing, Computer Vision, or Reinforcement Learning
  • In-depth understanding of both discriminative and generative AI algorithms and architectures
  • Experience designing and implementing end-to-end AI/ML pipelines for production environments
  • Familiarity with large language models (LLMs) and their applications

Programming and Data Analysis:

  • Strong proficiency in Python, including data analysis libraries (Pandas, NumPy, Scikit-learn)
  • Experience with AI/ML frameworks such as TensorFlow, PyTorch, or Keras
  • Proficient in SQL for data extraction and analysis
  • Familiarity with data visualization tools (e.g., Matplotlib, Seaborn)

Cloud and Data Engineering:

  • Working knowledge of cloud platforms, preferably Google Cloud Platform (GCP)
  • Experience with data pipelines and ETL processes
  • Basic understanding of MLOps practices and model deployment

Preferred Technical Skills:

  • Familiarity with GCP AI/ML services (e.g., Vertex AI)
  • Experience with deployment frameworks like FastAPI or Streamlit
  • Knowledge of version control systems (e.g., Git)
  • Basic understanding of containerization (Docker)
  • Familiarity with Large Language Models (LLMs), RAG (Retrieval-Augmented Generation), vector databases, and document embeddings
  • Expertise in prompt engineering and knowledge of cutting-edge AI tools and frameworks

Soft Skills:

  • Excellent problem-solving abilities and analytical thinking
  • Strong communication skills, able to explain complex technical concepts to both technical and non-technical stakeholders
  • Ability to translate business requirements into technical solutions and align AI initiatives with organizational goals
  • Experience working in cross-functional teams and collaborating with diverse stakeholders
  • Self-motivated with a passion for continuous learning in the rapidly evolving field of AI/ML
  • Project management skills, including experience with Agile methodologies
  • Ability to write clear, concise technical documentation and reports

What will you do:

  • Assist in developing user training modules and extending AI Agent capabilities for various business processes.
  • Support the development and integration of AI solutions for loan underwriting, including document verification and credit scoring models.
  • Implement and maintain current deployed AI models for internal Paper users.
  • Conduct research and development on advanced AI and LLM technologies to drive innovation and implementation.
  • Prototype and test new algorithms and models to solve complex business problems.
  • Work closely with cross-functional teams, including product design, engineering, and business stakeholders, to understand and meet their data needs.
  • Document AI models, algorithms, and systems to ensure knowledge sharing and reproducibility.
  • Participate in code reviews and provide feedback to improve code quality and best practices.

Technical Skills:

AI and Machine Learning:

  • Strong proficiency in developing and deploying AI/ML models, with expertise in one or more areas: Machine Learning, Natural Language Processing, Computer Vision, or Reinforcement Learning
  • In-depth understanding of both discriminative and generative AI algorithms and architectures
  • Experience designing and implementing end-to-end AI/ML pipelines for production environments
  • Familiarity with large language models (LLMs) and their applications

Programming and Data Analysis:

  • Strong proficiency in Python, including data analysis libraries (Pandas, NumPy, Scikit-learn)
  • Experience with AI/ML frameworks such as TensorFlow, PyTorch, or Keras
  • Proficient in SQL for data extraction and analysis
  • Familiarity with data visualization tools (e.g., Matplotlib, Seaborn)

Cloud and Data Engineering:

  • Working knowledge of cloud platforms, preferably Google Cloud Platform (GCP)
  • Experience with data pipelines and ETL processes
  • Basic understanding of MLOps practices and model deployment

Preferred Technical Skills:

  • Familiarity with GCP AI/ML services (e.g., Vertex AI)
  • Experience with deployment frameworks like FastAPI or Streamlit
  • Knowledge of version control systems (e.g., Git)
  • Basic understanding of containerization (Docker)
  • Familiarity with Large Language Models (LLMs), RAG (Retrieval-Augmented Generation), vector databases, and document embeddings
  • Expertise in prompt engineering and knowledge of cutting-edge AI tools and frameworks

Soft Skills:

  • Excellent problem-solving abilities and analytical thinking
  • Strong communication skills, able to explain complex technical concepts to both technical and non-technical stakeholders
  • Ability to translate business requirements into technical solutions and align AI initiatives with organizational goals
  • Experience working in cross-functional teams and collaborating with diverse stakeholders
  • Self-motivated with a passion for continuous learning in the rapidly evolving field of AI/ML
  • Project management skills, including experience with Agile methodologies
  • Ability to write clear, concise technical documentation and reports

What will you do:

  • Assist in developing user training modules and extending AI Agent capabilities for various business processes.
  • Support the development and integration of AI solutions for loan underwriting, including document verification and credit scoring models.
  • Implement and maintain current deployed AI models for internal Paper users.
  • Conduct research and development on advanced AI and LLM technologies to drive innovation and implementation.
  • Prototype and test new algorithms and models to solve complex business problems.
  • Work closely with cross-functional teams, including product design, engineering, and business stakeholders, to understand and meet their data needs.
  • Document AI models, algorithms, and systems to ensure knowledge sharing and reproducibility.
  • Participate in code reviews and provide feedback to improve code quality and best practices.