SA - Data Scientist

SA - Data ScientistLocation: 100% RemoteIf your candidate is a fit, do complete the skills matrix with specific examples of their pertinent experience. If you simply provide years of experience that candidate will not be considered. Thank you.Skills MatrixRequired Skills - Examples of Candidate's Qualification(s)Natural Language Processing (NLP) P5 – MasterArtificial Intelligence (AI) P5 – MasterPython Frameworks P5 – MasterPlease use this space to highlight additional skills or relevant certifications applicable to the requirements of the specific role the candidate is being submitted for:P1 – Beginner (0-2 yrs experience) P2 – Intermediate (3-5 yrs experience) P3 – Advanced (7-10 yrs experience P4 – Expert (10+ yrs experience)Software Engineer:We are seeking a skilled Data Scientist with deep expertise in developing, fine-tuning, and integrating AI models, particularly in natural language processing (NLP). This role will focus heavily on analyzing unstructured medical records, developing AI models for extracting insights, and incorporating human-in-the-loop feedback to improve model performance. You will work closely with software engineers and other stakeholders to ensure that AI solutions are effectively integrated into the overall system architecture.Required Qualifications & Experience:Preferred Qualifications:

• Experience in healthcare, particularly working with unstructured medical records in clinical settings, leveraging NLP models for information extraction
• Experience working with human-in-the-loop systems, incorporating clinician/end-user feedback to improve AI model accuracy
• Educational background or practical training in a clinical setting, with exposure to clinical workflows and medical terminologies
• Familiarity with deep learning techniques, attention mechanisms, and transformers applied to healthcare data• 5+ years of experience in AI/Client development with a strong focus on NLP using frameworks such as TensorFlow, PyTorch, and Hugging Face
• Expertise in Python, with experience in libraries like Transformers, NLTK, SpaCy, Gensim, and data manipulation tools such as Pandas and NumPy
• Experience working with human-in-the-loop systems, integrating clinician feedback to refine AI models
• Ability to effectively articulate technical challenges and solutions
• Strong communicator with excellent written and verbal communication skills
• Knowledge about Agile development Methodologies.
• Identify and analyze user requirements to generate stories and tasks for team backlog
• Prioritize and execute tasks throughout the software development life cycle
• Create custom NLP algorithms and annotators to evaluate medical record data
• Create custom tools to enable analysts to perform data research
• Solid understanding of statistical modeling, data analysis, and performance evaluation metrics.
• Demonstrated experience analyzing and processing unstructured clinical data (e.g., electronic health records, physician notes, imaging reports), using techniques such as tokenization, lemmatization, and word embeddings (e.g., TF-IDF, BERT)
• Familiarity with healthcare data formats and standards such as HL7, FHIR, ICD codes, and SNOMED
• Experience with cloud platforms (AWS, Azure), containerization (Docker), and using CI/CD pipelines for machine learning model deployment
• Knowledge of SQL (PostgreSQL, MySQL) and NoSQL (MongoDB, Elasticsearch) databases, and how to structure data pipelines for efficient data processing
• Develop and fine-tune AI models for natural language processing (NLP) tasks, including Named Entity Recognition (NER), text classification, and sentiment analysis, particularly with unstructured clinical records
• Conduct experiments to evaluate model performance, utilizing metrics such as precision, recall, and F1-score to iteratively improve models through hyperparameter tuning and training optimizations
• Analyze and preprocess large datasets, particularly unstructured medical records (e.g., physician notes, discharge summaries), using tools like Pandas, NLTK, and SpaCy• Master's degree (Data Science, AI, Computer Science, or a related field) + 10 years experience; or PhD + 4 years