New York, New York, 10007

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Onsite

Job Summary

We are on the lookout for a talented Computational Biologist with a strong focus on artificial intelligence to contribute to innovative public health solutions. This position is fully remote and involves leveraging data analysis and computational models to support and enhance various health initiatives. The ideal candidate will play a crucial role in analyzing biological data and developing predictive models that drive public health strategies.

Responsibilities

  • Analyze complex biological and health-related datasets to extract actionable insights.
  • Develop, implement, and optimize computational models to predict health trends.
  • Collaborate with cross-functional teams, including data scientists and public health experts, to enhance ongoing research projects.
  • Utilize machine learning techniques to improve data analysis processes and results.
  • Prepare and present findings to stakeholders in an understandable form.
  • Stay updated with the latest advancements in computational biology and AI technologies.

Qualifications

  • A degree in Computational Biology, Bioinformatics, or a related field.
  • Proven experience in data analysis and model building, preferably in the public health sector.
  • Familiarity with machine learning algorithms and tools.
  • Strong programming skills in languages such as Python or R.
  • Excellent analytical and problem-solving capabilities.
  • Effective communication skills to convey complex information clearly.

DataAnnotation provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
To apply for this job, please upload your resume.
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Remote Computational Biologist for AI-Driven Public Health
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supports..pdf, .doc, .docx, or .txt file