IT Data Scientist
Job Description
Advocates and educates on the value of data-driven decision-making, focusing on the “how and why” of solving problems.
Leads the life cycle of data science projects, from analysis, build, train, validate, and deploy.
Creates iterative, interpretable, dynamic, and scalable models seamlessly incorporated into analytic data products based on feedback from multiple stakeholders.
Engineers features using business acumen to combine disparate internal and external structured and unstructured data sets and sources.
Follows best practices for developing analytic methodologies and software.
Formulates validation strategies to ensure accurate and reliable data.
Develops and implements new algorithms for processing and imputing clinical, financial, and operational data in collaboration with internal technical and engineering teams.
Performs deep analytics and generates reports with recommended solutions around various topic areas.
Serves as a member in AI governance initiatives to enhance transparency, accountability, safety, reliability, and ethical standards.
Identifies data abnormalities and their root causes, suggesting possible steps for mitigation.
Transforms large amounts of complex data into business insights and solutions using statistics, machine learning, pattern recognition, text mining, and parallel/distributed computing.
Utilizes the latest technologies and tools in AI, NLP, and LLM to develop prototypes for business and deploy them in production.
Knowledge, Skills, And Abilities
- Healthcare Business Acumen & Industry Knowledge: [Required]
- Research work experience [Required]
- Strong record of healthcare data science experience with demonstrated results [Required]
- Ability to approach high-level challenges with a clear eye on what is important; employing the right approach/methods to make the maximum use of time and human resources. [Required]
- Experience working with a healthcare data platform such as the Epic and Cerner [Required]
- Experience working in a large healthcare system a strong plus [Required]
- Effective Communication: [Required]
- Proficient at detailing techniques and discoveries to technical and non-technical audiences in a language they can understand. [Required]
- Demonstrated ability to write scholarly publications [Required]
- Quantitative/Technical Skills: [Required]
- 5+ years of relevant experience in Data Science [Required]
- 3+ years of relevant experience in Health Care field [Required]
- Experienced in LLM (GPT, Mistral, Flan, Falcon, etc.) and NLP models (transformers), Encoders and Decoders [Required]
- Programming Languages: Python, Pandas, SQL, R [Required]
- Knowledgeable in frameworks such as PyTorch, TensorFlow, Huggingface, Langchain, Scikit-learn [Required]
- Experienced in MLOps using Docker, Flask, MLFlow, Git, Kubernetes, AWS, Linux, etc. [Required]
- Knowledgeable in PowerBI using DAX [Required]
- Proficient in deep learning techniques such as CNN, RNN, OCR [Required]
- Highly competent in advanced statistical modeling and implementation of machine learning algorithms (Logistic, Bayesian, Decision Trees, Random Forest, Gradient Boosting, Neural Networks, etc.) [Required]
- Proficient in Azure ML platform, Endpoint development and Deployment [Required]
- Competent in Cloud-based computing and data integration services (MS Azure, Data Factory, Snowflake) [Required]
- Intellectual Curiosity; Proficient at exploring new territories and finding creative and unusual ways to solve problems [Required]
- Self-motivated, independent and goal-oriented, a fast learner with good communication skills. [Required]
Education
- Master's [Required]
- Field Of Study in Data Science, Computer Science, Statistics, Artificial Intelligence, Quantitative Methods, or closely related quantitative field [Required]
Work Experience
- 5 years of relevant experience in data science and unsupervised research [Required]
Physical Requirements
View physical requirements
Pay Range
$83,699.48 - $155,693.55