Data Scientist

Data Scientist at North Star Staffing

We are seeking an experienced Data Scientist to drive innovation through advanced analytics and modeling of high-dimensional biosensor data. This remote role will contribute directly to biosensing research and development, enabling next-generation product improvements and prototype development.

The ideal candidate combines strong statistical and machine learning expertise with hands-on experience in hardware sensor data, signal processing, and experimental analysis.

Key Responsibilities

• Advanced Data Analysis & Modeling: Execute, debug, and optimize distributed compute workflows for large-scale metric computation and modeling. Apply statistical analysis, machine learning, and advanced mathematical methods to uncover patterns in biosensor datasets. Design and develop predictive models to extract actionable insights from real-world sensor data.
• Signal Processing & Sensor Analytics: Analyze time-domain signals and/or medical imaging data. Apply signal processing techniques to improve data interpretation and model performance. Support hardware sensor data analysis and prototype validation.
• Experimentation & Hypothesis Testing: Generate and test hypotheses through structured product experimentation. Interpret experimental results to inform product and R&D strategy.
• Cross-Functional Collaboration: Partner with engineering teams to translate analytical prototypes into scalable product solutions. Provide technical guidance for large-scale deployment of models and analytics frameworks.
• Visualization & Communication: Develop visualizations to communicate insights clearly to technical and non-technical stakeholders. Present findings from statistical and machine learning analyses to diverse audiences.

Minimum Qualifications

• Master’s or PhD in Computer Science, Statistics, Neuroscience, Biomedical Engineering, or related field.
• 3+ years of experience in data extraction, manipulation, and visualization.
• Strong proficiency in Python, R, MATLAB, and/or SQL.
• Experience working with large-scale datasets.
• Strong understanding of data structures and algorithms.

Required Technical Skills

• Experience with hardware sensor data and real-world signal analysis.
• Signal processing expertise (time-domain signals and/or medical imaging systems).
• Scientific computing libraries: NumPy, SciPy, Pandas, Scikit-learn, dplyr, caret.
• Data visualization tools: Matplotlib, Pyplot, seaborn, ggplot2.
• Machine learning and predictive modeling techniques.

Core Competencies

• Advanced Statistical Analysis
• Machine Learning & Predictive Modeling
• Signal Processing
• Experimental Design
• Distributed Compute Workflows
• Cross-Functional Technical Collaboration

Work Environment

This is a remote, research-driven, data-intensive environment with close collaboration with hardware and engineering teams.

Key skills/competency

• Biosensor Data
• Machine Learning
• Signal Processing
• Statistical Analysis
• Predictive Modeling
• Python
• Data Visualization
• Distributed Computing
• Hardware Sensors
• Experimental Design