Algorithm Scientist

Jobtailor; San Francisco (CA); On-site; USD 120,000 - 180,000; Full time

Job summary

Jobtailor is seeking a skilled biosignal processing specialist to implement and benchmark time-series ML algorithms for multimodal signals such as PPG, motion, and temperature.

You will collaborate with hardware, firmware, and software teams to refine data collection pipelines and ensure robust preprocessing of noisy real-world data. Strong communication of complex results to cross-functional teams is essential.

Qualifications

• 2–4+ years of practical experience in biosignal processing, time-series analysis, or sensor fusion.
• Strong expertise in Python and scientific computing libraries (NumPy, SciPy, pandas, scikit-learn, PyTorch/TensorFlow).
• Solid foundational understanding of human physiological systems and biosensing techniques.
• Practical experience with noisy, real-world time-series data and robust preprocessing pipelines.
• Master’s degree or PhD in Biomedical Engineering, Signal Processing, Machine Learning, Electrical Engineering, or related quantitative field.
• Strong analytical skills and ability to explain complex data and methods to cross-functional peers.

Responsibilities

• Implement, refine, and benchmark signal processing and machine learning algorithms for multimodal biosignals (PPG, motion, temperature).
• Apply signal cleaning, noise reduction, feature extraction, and time-series data integration across modalities.
• Collaborate with hardware, firmware, and software teams to optimize data collection pipelines.
• Analyze data from prototype sensors and benchtop setups to assess algorithmic feasibility and signal integrity.
• Analyze time-series datasets to discover relationships between signal features and physiological states.
• Document findings and present results to project leads and cross-functional teammates.

Skills

Biosignal Processing

Time-Series Analysis

Python Programming

Machine Learning Algorithms

Data Cleaning and Preprocessing

Education

Master’s degree in Biomedical Engineering

PhD in Signal Processing

Tools

NumPy

SciPy

Pandas

Scikit-learn

PyTorch

TensorFlow

Job description

• Implement, refine, and benchmark signal processing and machine learning algorithms for multimodal biosignals, including PPG, motion, and temperature
• Apply signal cleaning, noise reduction, feature extraction, and time-series data integration across novel modalities
• Collaborate with hardware, firmware, and software engineering teams to analyze sensor performance and optimize data collection pipelines
• Analyze data from prototype sensors, evaluation kits, and benchtop setups to assess algorithmic feasibility and signal integrity
• Analyze time-series datasets to discover relationships between physical signal features and underlying physiological states
• Document technical findings, present experimental results, and communicate data-driven insights to project leads and cross-functional teammates

Requirements

• 2–4+ years of practical experience (including advanced degree research) in biosignal processing, time-series analysis, or sensor fusion
• Strong expertise in Python and scientific computing libraries (NumPy, SciPy, pandas, scikit-learn, PyTorch/TensorFlow)
• Solid foundational understanding of human physiological systems and biosensing techniques
• Practical experience working with noisy, real-world time-series data and designing robust preprocessing pipelines
• Master’s degree or PhD in Biomedical Engineering, Signal Processing, Machine Learning, Electrical Engineering, or a related quantitative field
• Strong analytical skills with the ability to clearly explain complex data, methodologies, and technical results to cross-functional peers

Core Competencies

Demonstrates expertise in biosignal processing and time-series analysis, with a strong foundation in Python and scientific computing libraries. Capable of collaborating across engineering teams to optimize data collection and analyze complex datasets for insights into physiological states.

Highest-signal resume keywords

• Biosignal Processing
• Time-Series Analysis
• Python Programming
• Machine Learning Algorithms
• Data Cleaning and Preprocessing

Hard Skills

• Signal Processing
• Feature Extraction
• Noise Reduction
• Sensor Fusion
• Data Integration
• Statistical Analysis
• Algorithm Development
• Experimental Design
• Data Visualization
• Technical Documentation

Soft Skills

• Analytical Skills
• Communication Skills
• Collaboration
• Problem-Solving

Certifications & Qualifications

• Master’s Degree in Biomedical Engineering
• PhD in Signal Processing

Industry Keywords

• Biosensing Techniques
• Physiological States
• Sensor Performance
• Data Collection Pipelines
• Multimodal Biosignals

Tools & Technologies

• NumPy
• SciPy
• Pandas
• Scikit-learn
• PyTorch
• TensorFlow