Data Scientist
Skills
GithubGoogle Cloud PlatformHL7 StandardsLarge Language ModelsNatural Language ProcessingPythonStatistical Data Analysis
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- Bachelor’s degree in Computer Science, Engineering, Physics, Statistics, Applied Math, or other quantitative fields with minimum 2 years experience in quantitative analysis or data science
- Experience with LLMs and implementing them in practical applications
- Proficient in exploring complex data sets and extracting value using ETL and ad-hoc scripting
- Ability to work collaboratively and independently
- Familiarity with software tools like Git and unit/integration testing
- Experienced with query languages and SQL databases
- Functional experience with Cloud platforms like AWS or GCP
- Experience with data visualization tools like Streamlit and matplotlib
- Proficient coding skills in Python
- Ability to quickly learn and support existing products
- Experience in the healthcare industry and familiarity with DICOM and HL7 data is desirable
- Experience communicating technical concepts to technical and non-technical audiences
Nice to have
- Creative thinker
- Problem solver
- Experience in healthcare
- Familiar with DICOM and HL7 data
- Strong communicator
Day to day
- Discover business narratives told by the data and communicate them to other teammates.
- Perform data exploration and data mining to create large datasets for evaluating, improving, or fine-tuning large language models (LLMs).
- Design, develop, and optimize prompts for various applications to ensure effective use of large language models (LLMs).
- Collaborate with cross-functional teams to integrate LLMs into different applications and workflows.
- Conduct complex statistical analyses using Python libraries like NumPy, SciPy, and Statsmodels.
- Contribute code and participate in code reviews for production software solutions.
- Apply test-driven development and data-driven QA for quality software creation.
- Identify and implement automation solutions to increase team efficiency.
- Use Agile methodology for iterative progress towards goals while maintaining accessibility to current implementations.