Machine Learning Data Scientist

Pyyne; New York (NY); Hybrid; USD 130,000 - 150,000; Full time

Job summary

Pyyne is seeking a mid-level Data Scientist in New York, specializing in the biopharma sector. This hybrid role focuses on improving patient outcomes through ML, involving model development, collaboration with clinical experts, and clear communication of findings to stakeholders.

Benefits

Flexible hybrid working environment

Health and wellness benefits

Career development opportunities

Qualifications

• Mid-level Data Scientist with experience in the biopharma sector.
• Experience must include Python and SQL for ML.

Responsibilities

• Develop and validate machine learning models for early indicators of diseases.
• Collaborate with clinical experts to interpret model results.

Skills

Python

SQL

Job description

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Pyyne is a modern technology consultancy engineering the next generation of digital products and services.

At Pyyne, we believe in using technology to unlock business potential, create sustainable growth, and drive forward digital excellence. Our solutions range from advanced Software Engineering, Cloud, and Data & AI solutions.

Job Summary

Pyyne is seeking a mid-level Data Scientist with experience in the biopharma sector to work as a consultant out of our New York Office. This is a high-impact role for Pyyne as we rapidly expand our Data Science practice globally.

Ultimately, a successful candidate in this role will guide better treatment pathways and improve patient outcomes through improved end-to-end ML model development and deployment in a clinical setting. The ideal candidate is motivated to make a difference in people’s health through Machine Learning and is excited to work in a consulting and implementation capacity with our clients to make that happen.

This is a Hybrid Role in New York City, 3 days a week in-person. The salary range for this role is between 130k-150k annually commensurate with experience.

Key Responsibilities

• Develop and validate machine learning models to identify early indicators of rare diseases from structured and unstructured data sources
• Work with clinical experts to interpret model results and refine features based on medical relevance
• Collaborate with data engineering to optimize pipelines for data transformation, ingestion, and model deployment
• Translate complex findings into clear insights for stakeholders through dashboards, reports, and presentations
• Ensure model interpretability and adherence to ethical AI practices in a regulated healthcare environment

Must Have Skills

• Python (for ML, Pandas, Pytorch),
• SQL (Advanced skills including joins, aggregation, window functions, CTEs)

Nice to Have Skills

• Experience working with clinical or claims data, patient phenotyping, or real-world evidence generation
• Familiarity with healthcare data privacy standards (e.g., HIPAA, GDPR)
• Knowledge of Spark or distributed computing tools
• Familiarity with visualization tools like Power BI or Tableau
• Experience with model monitoring and MLOps tools
• Experience in end-to-end ML model development and deployment in a clinical setting
• Strong communication skills with both technical and non-technical audiences
• Demonstrated collaboration with data engineering or software engineering teams
• Familiarity with Explainable AI (XAI) or fairness in ML techniques
• Salary Range from 130-150k
• A flexible hybrid working environment.
• Health and wellness benefits.
• Career development opportunities in a fast-growing company.

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

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