Job Description
Join our team as a Data Scientist, where you'll play a crucial role in transforming vast amounts of patient and environmental data into actionable insights. Your expertise will help us advance clinical and research outcomes, making a positive impact in the healthcare sector.
Key Responsibilities:
Collaborate with research teams to design and implement analysis specifications, including input data requirements, data cleaning processes, algorithms, and interpretation of results.
Develop and apply algorithms to existing data warehouse records, while identifying new external data sources to enhance our analyses.
Conduct analyses addressing a wide range of clinical and research outcomes.
Research and implement AI algorithms, utilizing off-the-shelf AI and data-centric tools, while managing the collection, storage, and maintenance of data.
Demonstrate your expertise by developing scalable artificial intelligence systems that involve collaboration across multiple teams.
What You Bring:
Programming Skills:
Proficient in Python for data analysis, machine learning, and scripting.
Experience with SQL for effective database querying and management.
Familiarity with SAS for healthcare data analysis.
Knowledge of MATLAB for algorithm development (less common in healthcare).
Experience with R for statistical computing and bioinformatics.
Data Science & Machine Learning Frameworks:
Proficient with frameworks such as TensorFlow, PyTorch, and Keras for deep learning and advanced AI.
Experience with Scikit-Learn for classical machine learning.
Familiarity with gradient boosting techniques using XGBoost or LightGBM.
Knowledge of Large Language Models (LLMs) for text generation and summarization.
Experience with AWS SageMaker for end-to-end machine learning development.
Understanding of Natural Language Processing (NLP) tools and frameworks (e.g., Hugging Face).
Familiarity with AWS Bedrock for accessing pre-trained LLMs.
Healthcare Knowledge:
Understanding of HL7 and FHIR standards for electronic health information exchange.
Familiarity with ICD-10 coding for medical diagnosis and procedure classification.
Knowledge of HIPAA compliance to ensure secure handling of sensitive patient data.
Familiarity with clinical terminologies such as SNOMED and LOINC.
Data Tools & Platforms:
Experience with SQL-based databases (e.g., PostgreSQL, MySQL).
Familiarity with data warehousing solutions (e.g., AWS Redshift, Google BigQuery).
Proficient in data visualization tools (e.g., Tableau, Power BI).
Knowledge of NoSQL databases (e.g., MongoDB).
Experience with big data processing using Apache Hadoop or Spark.
Familiarity with ETL tools (e.g., Informatica, AWS Glue).
Statistical & Analytical Techniques:
Proficient in various regression analyses and descriptive statistical tests.
Experience with clustering techniques and dimensionality reduction methods.
Knowledge of predictive modeling for patient outcomes and time series analysis.
Familiarity with A/B testing in clinical trials or health interventions.
Cloud Computing & DevOps Skills:
Experience with cloud platforms like AWS, Google Cloud, or Azure.
Familiarity with serverless computing using AWS Lambda.
Knowledge of containerization technologies (Docker, Kubernetes) for data applications.
Understanding of CI/CD pipelines for automating deployment of machine learning models.
Experience with Electronic Health Records (EHR):
Familiarity with popular EHR systems such as Epic or Cerner.
Data Governance & Security:
Understanding of data privacy laws, including HIPAA and GDPR.
Knowledge of data anonymization techniques for research compliance.
Familiarity with auditing and compliance tools for secure data handling.
Education:
Bachelor's degree in computer science, artificial intelligence, informatics, or a closely related field is required.
A master's degree is preferred.
Employment Type: Full-Time
Salary: $ 83,000.00 200,000.00 Per Year
Job Tags
Full time, Remote job,