Data & AI Engineer

AMARIS GROUP SA; Cambridge (MA); Híbrido; USD 120.000 - 180.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

International community

Internal Academy training

Team events and collaboration

Descripción de la vacante

AMARIS GROUP SA in Cambridge, MA is seeking a Data & AI Engineer to lead data engineering, analysis, and AI/ML initiatives in a healthcare tech environment. You will work with data, biomedical, IT, and engineering teams to ensure data is reliable, scalable, and ready for advanced analytics and AI solutions.

You will collaborate across sites, utilizing Python and AWS data services to build robust data platforms and predictive models, contributing to patient-centric healthcare outcomes.

Formación

• 7 to 10 years of professional experience in data engineering and data analysis.
• Hands-on AI/ML experience with predictive algorithms and models.
• Experience with healthcare data including EMR and physiological signals.
• Medical device industry background with device-generated data.
• Strong Python for data processing and ML.
• Bash scripting for batch processing and automation.
• Hands-on AWS data services experience (S3, Athena, SageMaker).
• Jupyter Notebooks for exploration and data investigation.
• Experience parsing CSV/XML into scalable databases; InfluxDB exposure.
• Identify and resolve data quality issues and root causes.
• Excellent collaboration across technical and non-technical stakeholders.

Responsabilidades

• Retrieve data from AWS S3 and analyze with Athena, SageMaker, and Jupyter Notebooks.
• Clean, transform, and prepare large datasets from multiple sources.
• Identify missing data, inconsistencies, and time-alignment issues.
• Develop and maintain data pipelines transforming CSV/XML into scalable databases.
• Automate ingestion, inventory, validation, and quality assessment of device data.
• Investigate data gaps and quality issues using analytical tools.
• Collaborate with biomedical, IT, and engineering teams to ensure reliable data.
• Model physiological, vital-sign, and EMR data to support AI/ML solutions.
• Cross-validate results with SAS in collaboration with biostatistics teams.
• Prepare retrospective data to generate simulated data for testing.

Conocimientos

Python

AI/ML

Data analysis

Data quality

Bash scripting

AWS data services

Jupyter Notebooks

Time-series data

Healthcare data

Device data

Herramientas

AWS S3

Athena

SageMaker

Jupyter Notebooks

InfluxDB

CSV/XML parsing

Descripción del empleo

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 theopportunity 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: United States (Cambridge (Massachusetts, US) or Canada (Ontario, GTA)
Work Mode:remote/ hybrid / onsite

Key Responsibilities:

• Retrieve data from AWS S3 and query and analyze datasets using Amazon Athena, SageMaker, and Jupyter Notebooks.
• Clean, transform, and prepare large datasets from multiple sources.
• Identify missing data, inconsistencies, time-alignment discrepancies, and artifact-prone measurements.

Data Management

• 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.

Data Integrity Evaluation

• Investigate data gaps, anomalies, and integrity issues using Athena, SageMaker, or Jupyter Notebooks.
• Determine whether root causes relate to data curation, technical configuration, system performance, or storage limitations.

Troubleshooting and Collaboration

• 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.

Data Modeling and AI/ML

• 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.

Statistical Validation

• Cross-validate Python-based machine learning and regression results against outputs generated in SAS, in collaboration with biostatistics teams.

Data Simulation

• 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.

Required Qualifications:

• 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 SageMaker.
• 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 time-series databases such as InfluxDB.
• Demonstrated ability to identify and resolve data quality issues, including missing data, time‑alignment problems, and measurement artifacts.
• Strong troubleshooting skills and the ability to diagnose root causes across data, configuration, and infrastructure.
• Excellent communication skills, with the ability to collaborate effectively with technical and non-technical stakeholders across multiple organizations.

Why choose us

• An international community bringing together more than 110 different nationalities
• An environment where trust is central: 70% of our leaders started their careers at the entry level
• A strong training system with our internal Academy and more than 250 modules available
• A dynamic work environment that frequently comes together for internal events (afterworks, team buildings, etc.)

Amaris Consulting promotes equal opportunities. We are committed to bringing together people from diverse backgrounds and creating an inclusive work environment. In this regard, we welcome applications from all qualified individuals, regardless of sex, sexual orientation, race, ethnicity, beliefs, age, marital status, disability, or other characteristics.