Forward Deploy Data Scientist
The Forward Deploy Data Scientist will partner with health systems and internal teams to investigate healthcare data, build and operationalize ML/LLM pipelines, and deliver actionable insights. The role requires 2–3 years of data science experience, strong Python and ML/NLP skills, and customer-facing communication ability.
About the job
Responsibilities
- Partner with health systems and hospital customers to understand their data, workflows, and goals, and share insights that demonstrate product value and identify opportunities.
- Design and execute data and machine learning investigations by validating and transforming large structured and unstructured healthcare datasets with state-of-the-art models.
- Deploy, build, and operationalize machine learning and large language model-based models and analytics pipelines with engineering and product teams.
- Collaborate with customer success and product teams to improve user engagement through data-driven analysis.
- Communicate results and insights clearly to technical, product, and clinical stakeholders.
- Build reusable playbooks, tools, and best practices to accelerate implementations and improve customer outcomes.
- Apply emerging machine learning, natural language processing, and healthcare data technologies to real-world clinical problems.
- Contribute to collaboration, innovation, and rigor across data science and product teams.
Requirements
- 2–3 years of professional experience in data science.
- Strong communication skills and comfort presenting to external customers.
- Strong programming skills in Python.
- Fluency with modern data science and machine learning/natural language processing libraries, such as PyTorch, TensorFlow, and Hugging Face.
- Experience with MLOps tools such as Airflow, MLflow, dbt, Docker, or cloud machine learning platforms.
- Familiarity with modern applied large language model techniques.
- Strong data manipulation, treatment, and evaluation skills, including the ability to efficiently and methodically wrangle large, complex datasets.
- Willingness to work hybrid 2–3 days per week from the Boston or NYC office.
Nice to Have
- Familiarity with Epic, Cerner, or other electronic health record systems.
- Experience in forward deployment, field data science, or consulting-style roles.
- Background in AI/machine learning for healthcare, clinical analytics, or real-world data.
Compensation
- Expected compensation range: $150,000–$180,000.
- Compensation depends on experience, overall fit, and candidate location.
Skills
Python, PyTorch, TensorFlow, Hugging Face, Airflow, MLflow, dbt, Docker, Machine Learning, Natural Language Processing, LLMs, Data Science, Epic, Cerner, Healthcare Data
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