Data & AI Engineer
Listed on 2026-10-07
-
IT/Tech
Data Engineering, Data Scientist, Machine Learning/ ML Engineer, Data Analyst
We are looking for a Data & AI Engineer to join our team and contribute to data engineering, analysis, and AI/ML initiatives within a healthcare technology environment
. The ideal candidate has strong experience working with large and complex datasets, data quality and transformation, Python-based data processing, and cloud data platforms.
You will work closely with data, biomedical, IT, and engineering teams to ensure data is reliable, scalable, and ready to support advanced analytics, predictive algorithms, and AI-driven solutions. The focus of this role is data engineering and analysis.
We offer the opportunity to work on data and AI initiatives that make a meaningful impact in healthcare technology.
Also, a collaborative environment spanning data, biomedical, IT, and engineering teams.
Location: Cambridge (Massachusetts, US)
Work Mode: on-site
Type of contract: C2C
- Retrieve data from AWS S3 and query and analyze datasets using Amazon Athena, Sage Maker, and Jupyter Notebooks.
- Clean, transform, and prepare large datasets from multiple sources.
- Identify missing data, inconsistencies, time-alignment discrepancies, and artifact-prone measurements.
- Develop and maintain data processing pipelines that transform and parse CSV, XML, and other flat-file formats into scalable databases and data structures such as InfluxDB.
- Develop and run Python and Bash scripts to automate ingestion, inventory, validation, and quality assessment of incoming device data.
- Investigate data gaps, anomalies, and integrity issues using Athena, Sage Maker, or Jupyter Notebooks.
- Determine whether root causes relate to data curation, technical configuration, system performance, or storage limitations.
- Collaborate with biomedical and IT teams at partner sites to troubleshoot data transfer and collection issues and ensure reliable data availability.
- Work closely with internal engineering, data, and technical teams to investigate and resolve data-related issues.
- Analyze and model physiological, vital-sign, and EMR data from multiple sources to support data-driven and AI/ML solutions.
- Develop, enhance, and evaluate predictive algorithms and machine learning models using multivariate data, including numerical and textual data.
- Cross-validate Python-based machine learning and regression results against outputs generated in SAS, in collaboration with biostatistics teams.
- Prepare and transform retrospective CSV/XML datasets to generate simulated data using a Virtual Hospital Simulator.
- Support algorithm testing and validation within surveillance software.
- Contribute to improving data quality, scalability, reliability, and analytical capabilities across data and AI initiatives.
- 7 to 10 years of professional experience in data engineering and data analysis
. - Hands-on AI/ML experience
, including developing, evaluating, and enhancing predictive algorithms and machine learning and regression models using multivariate data (numerical and text-based). - Experience with healthcare data
, including physiological signals, vital signs, and EMR data. - Background in the medical device industry
, including experience working with device-generated clinical data. - Strong proficiency in Python for data processing, analysis, and machine learning.
- Experience scripting in Bash for batch processing and automation.
- Hands-on experience with AWS data services
, including S3, Athena, and Sage Maker. - Experience working in Jupyter Notebooks for exploratory analysis and data investigation.
- Proven experience parsing and transforming flat-file formats (CSV, XML) into scalable databases, with exposure to…
(If this job is in fact in your jurisdiction, then you may be using a Proxy or VPN to access this site, and to progress further, you should change your connectivity to another mobile device or PC).