Senior Applied Scientist

At Koa Health, we are revolutionising mental health care by delivering therapeutic solutions through smartphones. Our mission is to make mental health support accessible, personalised, and effective by leveraging cutting-edge technology and data science.

Our R&D team has been at the forefront of applied precision medicine in digital mental health, with strong scientific contributions published in top-tier journals such as Nature Medicine, JMIR, npj Digital Medicine, Scientific Reports, and collaborations with leading institutions including the London School of Economics (LSE), Harvard Medical School, and the University of Oxford.

About the role

We are seeking a passionate and experienced Senior Applied Scientist to join our Research and Development team. The ideal candidate will have a strong background in data and statistical analysis, machine learning and LLMs with a keen interest in applying these skills to improve mental health outcomes.

You Will

• Data and Statistical Analysis:

  • Extract and preprocess features from smartphone sensor data (e.g., activity logs, screen on/off events, etc.) and app usage logs.
  • Perform time-series analysis to interpret different kinds of data (e.g., smartphone sensors, Electronic Health Records, app usage logs) to identify digital markers that correlated with mental health indicators.
  • Proficiency in statistical analysis for evidence generation, including hypothesis testing, and data interpretation.

• Machine Learning Algorithm Development:

  • Develop and implement machine learning models to infer the “right” therapy and/or the “right” moment of its delivery.
  • Build predictive algorithms to detect risks of symptom deterioration or lack of improvement.
  • Integrate LLMs to create classification/regression and content generation algorithms.

• Collaboration and Integration:

  • Work closely with cross-functional teams, including clinicians, engineers, and product managers, to integrate algorithms into the platform.
  • Communicate complex technical concepts to non-technical stakeholders effectively.

• Research and Development:

  • Stay updated with the latest advancements in digital mental health, machine learning, and digital phenotyping.
  • Work on early stage proof-of-concept projects alongside academic and medical institutions.
  • Publish and present research findings in scientific journals and conferences when applicable.

About You

• Education:

  • Master's in Computer Science, Data Science, Electrical Engineering, or a related field; Ph.D. preferred.

• Technical Skills:

  • Proficiency in Python.
  • Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn, LangChain).
  • Familiarity with version control systems such as Git.
  • Strong background in signal processing and time-series analysis.
  • Familiarity with handling data pipelines.

• Experience:

  • Experience in developing and deploying machine learning models in a production environment.
  • Prior work with sensor data and mobile platforms is highly desirable.
  • Strong publication and/or patent record is a plus.
  • Knowledge of mental health concepts and digital therapeutics is a plus.

• Soft Skills:

  • Excellent problem-solving abilities and analytical thinking.
  • Strong communication and teamwork skills.
  • Ability to work independently and manage multiple projects simultaneously