Job Description
Calmwave is seeking a skilled and motivated Data Scientist with expertise in time series forecasting research and deep learning to join our team. As a Data Scientist, you will play a critical role in leveraging our platform’s capabilities to augment clinical decisions in intensive care units (ICUs). You will be responsible for analyzing vital sign data (e.g., heart rate, blood pressure, medication inputs) and identifying breach conditions that lead to alarming ICU machines. Your insights will drive the development of our product by enhancing patient care and safety in high-stress healthcare environments.
Responsibilities
- Explore deep learning approaches aimed at uncovering patterns, optimizing predictions, and enabling intelligent decision-making by leveraging cutting-edge architectures and algorithms, including transformers.
- Experienced in transitioning machine learning models from the research stage to production environments, leveraging MLOps methodologies such as continuous integration/continuous deployment (CI/CD), version control with Git, automated testing, model monitoring, and model drift detection to ensure scalability, reproducibility, and seamless deployment in production.
- Conduct in-depth exploratory data analysis on vital sign time series data to identify regime states and extract meaningful features. Utilize statistical techniques to define breach events and develop a comprehensive understanding of their underlying characteristics.
- Define and implement statistical measures of volatility. Develop innovative methodologies to differentiate between volatile and non-volatile breaches, enhancing the explainability and interpretability of the analysis.
- Engineer relevant features from time series data to enrich the understanding of alarming events. Incorporate contextual information and additional data sources to enhance the analysis and support clinical decision-making.
- Perform co-variate analysis to identify correlations and relationships between breached threshold events and other variables, such as patient demographics, medical history, treatment interventions, and vital sign conditions.
- Collaborate closely with cross-functional teams, including data engineers, product managers, and clinicians, to translate findings into practical solutions and features within the platform.
Qualifications
- A strong background in data science, machine learning, artificial intelligence, statistics, or a related field, with a focus on time series analysis and healthcare analytics.
- Proficiency in programming languages such as Python and Julia, along with experience using relevant data manipulation and analysis libraries (e.g., scikit-learn, pandas) and SQL.
- Demonstrated experience in exploratory data analysis, feature engineering, and statistical modeling techniques applied to time series data, including machine learning models, Bayesian structural time series, state-space models, Seq2Seq models, or transformer-based models.
- Familiarity with classical statistical methods and measures used in defining volatility.
Strong communication skills, with the ability to convey complex technical concepts to both technical and non-technical stakeholders. - Experience in healthcare or data engineering is preferred. A bonus would be a solid understanding of clinical workflows and healthcare data systems.
- Ability to work in a fast-paced, collaborative environment, handling ambiguity and adapting to evolving requirements.
- If you are passionate about leveraging data science and analytics to revolutionize healthcare decision-making, we invite you to join our team at Calmwave.
Benefits
We offer excellent benefits, including health insurance, 401k, and more. If you are a highly motivated self-starter with a passion for healthcare and technology and are looking to join a growing company dedicated to making a positive impact in the world, please submit your resume and a cover letter for consideration to careers@calmwave.ai.