Data Scientist

Senior Data Scientist (NLP & LLM)

ARC Innovation Center

Situated on the Sheba Medical Center campus, with its world-leading clinical sites and research facilities, the ARC Innovation Center features an advanced and sophisticated environment that allows all partners to come together under one roof. It is a place where clinicians work shoulder to shoulder with developers, identifying unmet clinical needs and then, through rapid development cycles (up to a year from idea to initial proof of concept), develop solutions and products that can be brought to market.

Job Overview

We are looking for a highly skilled Senior Data Scientist with a strong background in Natural Language Processing (NLP) and Large Language Models (LLMs) to join our healthcare technology team. In this role, you will leverage advanced NLP techniques to extract insights from clinical data, improve patient outcomes, and support data-driven decision-making in healthcare.

Key Responsibilities

Model DevelopJob Title: Senior Data Scientist (NLP & LLM)

ARC Innovation Center

Situated on the Sheba Medical Center campus, with its world-leading clinical sites and research facilities, the ARC Innovation Center features an advanced and sophisticated environment that allows all partners to come together under one roof. It is a place where clinicians work shoulder to shoulder with developers, identifying unmet clinical needs and then, through rapid development cycles (up to a year from idea to initial proof of concept), develop solutions and products that can be brought to market.

Job Overview

We are looking for a highly skilled Senior Data Scientist with a strong background in Natural Language Processing (NLP) and Large Language Models (LLMs) to join our healthcare technology team. In this role, you will leverage advanced NLP techniques to extract insights from clinical data, improve patient outcomes, and support data-driven decision-making in healthcare.

Key Responsibilities

• Model Development: Design, implement, and optimize NLP models and LLMs tailored for healthcare applications, including clinical documentation, patient communication, and predictive analytics.
• Data Analysis: Analyze and preprocess large volumes of unstructured clinical data (e.g., EHRs, clinical notes) to ensure high-quality input for model training and evaluation.
• Research and Innovation: Stay current with the latest advancements in NLP and LLMs, and apply state-of-the-art techniques to address complex healthcare challenges.
• Mentorship: Provide guidance and mentorship to junior data scientists, fostering a culture of learning and collaboration within the team.
• Validation: Conduct experiments to evaluate model performance, using techniques such as A/B testing and cross-validation for continuous improvement.
• Collaboration: Work closely with cross-functional teams, including product managers, software engineers, and domain experts, to integrate NLP solutions into applications and services.
• Documentation and Reporting: Maintain comprehensive documentation of methodologies, findings, and best practices. Present findings and actionable insights to stakeholders, including clinical teams and leadership.

Qualifications

• Education: Bachelor’s or Master’s degree in Computer Science, Data Science or a related field (Ph.D. is an advantage).
• Experience: 5+ years of experience in data science, with a focus on NLP and LLMs.
• Technical Skills:
• Proficiency in programming languages such as Python and R.
• Experience with NLP libraries and frameworks (e.g., Hugging Face Transformers, SpaCy, NLTK).
• Strong understanding of machine learning and deep learning techniques, particularly in the context of healthcare data.
• Analytical Skills: Strong problem-solving abilities and experience with large text datasets.
• Communication: Excellent verbal and written communication skills, capable of conveying complex concepts to technical and non-technical audiences.
• Languages: Fluency in Hebrew and English.

Preferred Qualifications

• Experience with deploying NLP models in production environments.
• Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker).
• Knowledge of ethical considerations and best practices in AI applications in healthcare.
• ment: Design, implement, and optimize NLP models and LLMs tailored for healthcare applications, including clinical documentation, patient communication, and predictive analytics.
• Data Analysis: Analyze and preprocess large volumes of unstructured clinical data (e.g., EHRs, clinical notes) to ensure high-quality input for model training and evaluation.
• Research and Innovation: Stay current with the latest advancements in NLP and LLMs, and apply state-of-the-art techniques to address complex healthcare challenges.
• Mentorship: Provide guidance and mentorship to junior data scientists, fostering a culture of learning and collaboration within the team.
• Validation: Conduct experiments to evaluate model performance, using techniques such as A/B testing and cross-validation for continuous improvement.
• Collaboration: Work closely with cross-functional teams, including product managers, software engineers, and domain experts, to integrate NLP solutions into applications and services.
• Documentation and Reporting: Maintain comprehensive documentation of methodologies, findings, and best practices. Present findings and actionable insights to stakeholders, including clinical teams and leadership.

Qualifications

• Education: Bachelor’s or Master’s degree in Computer Science, Data Science or a related field (Ph.D. is an advantage).
• Experience: 5+ years of experience in data science, with a focus on NLP and LLMs.
• Technical Skills:
• Proficiency in programming languages such as Python and R.
• Experience with NLP libraries and frameworks (e.g., Hugging Face Transformers, SpaCy, NLTK).
• Strong understanding of machine learning and deep learning techniques, particularly in the context of healthcare data.
• Analytical Skills: Strong problem-solving abilities and experience with large text datasets.
• Communication: Excellent verbal and written communication skills, capable of conveying complex concepts to technical and non-technical audiences.
• Languages: Fluency in Hebrew and English.

Preferred Qualifications

• Experience with deploying NLP models in production environments.
• Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker).
• Knowledge of ethical considerations and best practices in AI applications in healthcare.