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Wearable Data Science Jobs in California (NOW HIRING)

January

Head of Partnerships

Menlo Park, CA · Remote

$200K - $300K/yr

... science, and real-world health data to empower individuals to take control of their health. Our flagship January app uses data from continuous glucose monitors, wearables, and food logs to predict ...

The Marlin Alliance

Sr Machine Learning Engineer

San Diego, CA · On-site

$110K - $152K/yr

Collaborate with engineers, data scientists, and mission stakeholders to align ML solutions with ... Ability to comply with Navy safety requirements and wear required personal protective equipment ...

The Marlin Alliance

Sr Machine Learning Engineer

San Diego, CA · On-site

$110K - $152K/yr

Collaborate with engineers, data scientists, and mission stakeholders to align ML solutions with ... Ability to comply with Navy safety requirements and wear required personal protective equipment ...

The Marlin Alliance

Sr Machine Learning Engineer

San Diego, CA · On-site

$131K - $173K/yr

Collaborate with engineers, data scientists, and mission stakeholders to align ML solutions with ... Ability to comply with Navy safety requirements and wear required personal protective equipment ...

Evidation

Senior/Lead Product Manager

Santa Barbara, CA · On-site

$175 - $250/hr

Evidation's privacy-centric digital health measurement and engagement platform uses data science ... Shape how Evidation collects, integrates, and applies multimodal health data (including wearables ...

Element Science

Senior Firmware Engineer

Redwood City, CA · On-site

$140K - $175K/yr

Element Science, Inc. is a medical device and digital health company redefining how patients with ... Our product, a wearable patch defibrillator, is designed for patients with a temporary elevated ...

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Wearable Data Science information

What is wearable data science?

Wearable data science is a field focused on analyzing and interpreting data collected from wearable devices such as smartwatches, fitness trackers, and health monitors. Professionals in this area develop methods to process large volumes of sensor data to gain insights into health, activity, and behavior patterns. The insights can be used to improve health outcomes, enhance user experiences, and support research in various domains including healthcare, sports, and consumer technology.

How do wearable data scientists typically collaborate with hardware engineers and software developers during product development?

Wearable data scientists work closely with hardware engineers to understand sensor specifications and data collection constraints, ensuring that the data is accurate and usable for analysis. They also collaborate with software developers to integrate data processing algorithms into wearable devices or companion apps, often providing feedback on data flow, storage, and real-time analytics. This cross-functional teamwork is essential for developing robust products that deliver actionable insights to users and meet technical requirements.

What are the key skills and qualifications needed to thrive as a wearable data scientist, and why are they important?

To thrive as a Wearable Data Scientist, you need a solid background in data analysis, statistics, machine learning, and a relevant degree in fields like computer science, engineering, or data science. Familiarity with programming languages such as Python or R, experience with data visualization tools, and knowledge of wearable sensor platforms are typically required. Strong problem-solving abilities, attention to detail, and effective communication skills help you translate complex data into actionable insights. These skills are vital for developing accurate models and delivering meaningful results that drive innovation in wearable technology.

What is the difference between Wearable Data Science vs Wearable Data Analyst?

AspectWearable Data ScienceWearable Data Analyst
Required CredentialsDegree in Data Science, Computer Science, or related field; knowledge of machine learningDegree in Data Analysis, Statistics, or related field; proficiency in data visualization tools
Work EnvironmentResearch labs, tech companies, healthcare startupsHealthcare providers, fitness companies, wearable device firms
Employer & Industry UsageDevelops algorithms, models, and wearable tech innovationsAnalyzes wearable data to inform decisions, improve products, and report findings

Wearable Data Science focuses on developing algorithms and models to interpret wearable device data, often involving machine learning. Wearable Data Analysts interpret and visualize this data to support business or healthcare decisions. Both roles require strong analytical skills but differ in technical depth and responsibilities.

What are popular job titles related to Wearable Data Science jobs in California?

For Wearable Data Science jobs in California, the most frequently searched job titles are:

What job categories do people searching Wearable Data Science jobs in California look for?

The top searched job categories for Wearable Data Science jobs in California are:

What cities in California are hiring for Wearable Data Science jobs?

Cities in California with the most Wearable Data Science job openings:

Wearable Data Science jobs near you
Infographic showing various Wearable Data Science job openings in California as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 13% Part Time, and 5% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution.

Machine Learning Engineer / UNICORN / Hybrid in SF

Motion Recruitment

San Francisco, CA

Full-time

Medical, Dental, Vision, PTO

Posted 14 days ago

Job description


A health technology company at the top of their industry is seeking a Machine Learning Engineer to join its research and development team. This full-time opportunity offers the chance to build advanced machine learning systems that power next-generation wearable and sensor-based health products. The team works heavily with Python, TensorFlow, PyTorch, Spark, signal processing, and large-scale physiological datasets to create meaningful consumer health insights.
This is a true zero-to-one engineering opportunity. Rather than maintaining existing models, this individual will help invent entirely new sensing capabilities, develop multimodal AI solutions, and influence the future roadmap of emerging health technologies. The organization values innovation, scientific rigor, and collaboration while providing significant ownership, rapid career growth, and the opportunity to see research move directly into production products used by customers worldwide.
Required Skills & Experience
  • 3+ years of machine learning engineering experience
  • Strong Python development experience
  • Experience with TensorFlow and/or PyTorch
  • Background working with sensor, wearable, physiological, or time-series data
  • Experience developing and deploying machine learning models
  • Understanding of signal processing techniques
  • Strong mathematical and statistical foundations
  • Bachelor's degree in Computer Science, Engineering, Mathematics, Data Science, or similar
Desired Skills & Experience
  • PhD in Machine Learning, AI, Computer Science, Statistics, Biomedical Engineering, or related field
  • Publications in top-tier ML conferences or journals
  • Experience with self-supervised learning
  • Experience with multimodal machine learning
  • Consumer wearable or medical device industry experience
  • Spark or distributed computing experience
  • Experience working with production-scale data pipelines
What You Will Be Doing
Tech Breakdown
  • 40% Machine Learning Development
  • 25% Signal Processing & Sensor Analytics
  • 20% Data Engineering & Spark
  • 15% Research & Experimentation

Daily Responsibilities
  • 80% Hands On Engineering
  • 20% Team Collaboration

The Offer
  • Competitive Salary
  • Equity Program
You will receive the following benefits:
  • Medical, Dental, and Vision Insurance
  • Generous PTO
  • Paid Holidays
  • Equity Participation
  • Career Development Opportunities

Applicants must be currently authorized to work in the US on a full-time basis now and in the future.
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