Alphatec Spine Company logo on Dataaxy
Alphatec Spine

Associate Data Scientist

πŸ“
Carlsbad, CA
πŸ§ͺ
Entry level
The Associate Data Scientist will join the Applied Research team within R&D at ATEC. In this role, you will leverage signal and image processing, machine learning, and statistical analysis to support the design and development of medical devices within the Alpha Informatix ecosystem. Your work will focus on advancing the innovative algorithms and automation behind EOS Insight, an end-to-end spine surgery platform, and SafeOp Neural InformatiX, an advanced intraoperative neuromonitoring system.

Essential Duties And Responsibilities

  • Partner with marketing and development teams to drive the use of algorithms, automation, and data science across the Alpha Informatix ecosystem
  • Participate in the development, documentation, validation and delivery of algorithms, models and software analysis tools
  • Use machine learning, signal/image processing and statistics in analyzing large, multimodal clinical and medical imaging datasets to extract actionable insights that inform{{{{:}}}} algorithm development, experimental design, and clinical or business decisions
  • Develop methods for data extraction, synthesis, labeling, visualization and analysis to learn from and enable algorithm prototyping with high volume, high dimensional datasets
  • Design experiments, A/B testing, evaluate the quality of derived assets and develop dashboards to communicate and continuously monitor performance
  • Communicate scientific findings and project status/risks/needs to both technical and non-technical audiences.

Requirements

The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

  • 1-3+ years of relevant work experience (academic or industry)
  • Proficient with one or more programing languages including Python, MATLAB or C++ including code documentation, version control and unit testing
  • Demonstrated success developing and deploying machine learning, signal processing, or medical image analysis algorithms in a professional setting (academic or industry)
  • Strong technical foundation in one or more of the following areas{{{{:}}}} signal processing, time series analysis, machine learning, multimodal learning, medical image analysis, high-order splines or statistics
  • Experience with physiological time series and/or medical imaging data highly desirable
  • Strong team player and highly collaborative

Education And Experience

  • Bachelors Degree in relevant quantitative (e.g. applied mathematics, engineering, physics) discipline
  • Minimum of 1 year experience in Data Science or Applied Research

For roles based in the United States that require access to hospital facilities, must be eligible for and maintain credentials at all required hospitals, including meeting any applicable physical requirements or vaccination requirements (including the COVID-19 vaccine, as applicable).

ATEC is committed to providing equal employment opportunities to its employees and applicants without regard to race, color, religion, national origin, age, sex, sexual orientation, gender identity, gender expression, or any other protected status in accordance with all applicable federal, state or local laws. Further, ATEC will make reasonable accommodations that are necessary to comply with disability discrimination laws.

Salary Range

Alphatec Spine, Inc. complies with state and federal wage and hour laws and compensation depends upon candidate's qualifications, education, skill set, years of experience, and internal equity. $82,000 to $90,000 Full-Time Annual Salary

Key informations

🧳
Full-time
πŸ“…
Posted 3 months ago

Don’t miss out on new
Data & AI Jobs

Get curated job alerts weekly.

Other jobs at Alphatec Spine

Alphatec Spine does not currently have any open job positions in Data & Ai.
© 2023 | All Rights Reserved | Built with 🀍 in MontrealAll our data is gathered from publicly available sources or contributed by users