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About the Role

Our client is looking for a highly skilled and experienced Remote Senior Data Scientist with a specialization in Machine Learning for Biological applications to join their distributed research team. This fully remote position offers the opportunity to work on complex biological datasets, developing predictive models and algorithms that drive breakthroughs in areas such as genomics, drug discovery, and precision medicine. You will collaborate closely with a global team of biologists, bioinformaticians, and software engineers, contributing your expertise to solve challenging scientific problems and translate data-driven insights into actionable strategies. The ideal candidate thrives in an autonomous, collaborative remote environment and possesses a deep passion for applying cutting-edge AI and ML techniques to biological challenges, making a significant impact from anywhere in the world.

Key Responsibilities

• Develop, implement, and deploy advanced machine learning models for analyzing large and complex biological datasets (e.g., genomic, proteomic, clinical).
• Design and execute computational experiments to identify patterns, predict outcomes, and uncover novel biological insights.
• Collaborate with biologists and researchers to define problem statements, extract relevant features, and interpret model results.
• Build scalable data pipelines and workflows for data preprocessing, feature engineering, and model training.
• Stay abreast of the latest advancements in machine learning, artificial intelligence, and their applications in biology.
• Communicate complex findings and methodologies clearly to both technical and non-technical stakeholders globally.

Requirements

• Ph.D. or M.Sc. in Data Science, Computer Science, Statistics, Bioinformatics, or a related quantitative field.
• Minimum of 5 years of professional experience in data science, with a significant focus on machine learning and its application to biological data .
• Strong programming skills in Python or R, with extensive experience using ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Proven experience in developing and deploying predictive models for classification, regression, clustering, or deep learning tasks.
• Familiarity with biological concepts, data types, and research areas is highly advantageous.
• Excellent communication, problem-solving, and collaboration skills for effective remote teamwork.

Benefits

• Highly competitive salary and potential for stock options or performance bonuses.
• Comprehensive health, dental, and vision insurance plans.
• Flexible and autonomous remote work environment with support for home office setup.
• Generous paid time off and company holidays.
• Opportunities for continuous learning, professional development, and attending virtual scientific conferences in machine learning .
• The chance to contribute to high-impact research with a globally recognized team from your own location.