Data Scientist
all around Latin America
Hourly savings
Annual Savings
Additional Savings
Basic Qualifications:
- 5+ years of experience in data science, machine learning, and AI model development.
- Proven experience with data ingestion, cleaning, and labeling, particularly with timestamped event data.
- Experience in developing and validating AI/ML algorithms, particularly for health applications (e.g. stress detection) and data characterization.
- Strong background in handling and analyzing biomarker and wearable sensor data, with a focus on time series data.
- Master's or PhD in Computer Science, Data Science, Machine Learning, Statistics, or a related field.
- Expertise in time series analysis and techniques for physiological data from health apps and sensors.
- Knowledge of data visualization tools and techniques.
Key Responsibilities:
- Data Ingestion and Cleaning: Develop robust pipelines for ingesting data from various wearable sensors and health apps, focusing on time series physiological data. Ensure data quality through cleaning and preprocessing steps, including handling missing data, normalization, and labeling based on event timestamps.
- Time Series Analysis: Apply advanced time series analysis techniques to understand physiological patterns and detect anomalies related to stress. Collaborate with domain experts to ensure the biological relevance of the developed models.
- Stress Detection and Characterization: Design and implement algorithms to detect and characterize stress levels from time series biomarkers and wearable data. Integrate stress detection models to provide real-time insights and recommendations.
- Prototype Development: Create a functional prototype for stress detection and management, integrating AI/ML models with web or mobile applications. Test and validate the prototype using training data sets or real-world data, iterating based on feedback and performance metrics.
- Collaboration and Reporting: Work closely with the startup founder to align on project goals and deliverables. Prepare and present progress reports, findings, and recommendations.
