Position: Data Scientist IV
Type: Full-time
Compensation: $80 – $110/hour
Location: New York, NY, USA (Onsite)
Commitment: Full-time
Role Responsibilities
• Execute, debug, and optimize distributed compute workflows for metric computation, analysis, and modeling across large and high-dimensional datasets.
• Apply advanced statistics, machine learning, programming, data modeling, simulation, and mathematical techniques to identify patterns, generate insights, and support biosensor product development.
• Design, develop, and evaluate predictive models and advanced algorithms to maximize value extraction from biosensor and sensor-based datasets.
• Generate, test, and analyze hypotheses through structured experimentation and interpret results to guide product and R&D decisions.
• Collaborate closely with engineering teams to translate analytical prototypes into scalable products, services, and features.
• Provide analytical guidance and recommendations for large-scale implementation of data-driven solutions.
• Leverage data visualization and exploratory analysis to inform strategic decisions around future biosensing research and development directions.
• Support continuous improvement of data pipelines, modeling approaches, and analytical methodologies.
Requirements
• Master’s or PhD degree in Computer Science, Statistics, Neuroscience, Biomedical Engineering, or a closely related field.
• Strong experience working with large-scale, real-world datasets, particularly sensor or biosensor data.
• Hands-on experience with signal processing in time-domain signals and/or medical imaging systems.
• Strong experience of performing data extraction, manipulation, modeling, and visualization using Python, R, MATLAB, or SQL.
• Proficiency in data structures, algorithms, and scientific computing methodologies.
• Experience with scientific computing and machine learning libraries such as NumPy, SciPy, Pandas, Scikit-learn, dplyr, and caret.
• Experience with data visualization libraries including Matplotlib, Pyplot, seaborn, or ggplot2.
• Strong ability to present statistical and machine learning findings to both technical and non-technical audiences.
• Excellent analytical, problem-solving, and collaboration skills.
Application Process
• Upload resume
• Interview (15–30 min)
• Submit form
