Senior Machine Learning Engineer

Job Description

Job Description

The Job Opportunity :

The Sr. Machine Learning Engineer will work closely with cross-functional product teams and build high-quality data pipelines for high-end analytics solutions.

These solutions will generate insights from the organization's connected data and enable data-driven decision-making capabilities for the organization.

This role will help develop standards, guidelines, and direction for data modeling and standardization that will directly contribute to enhancing the quality of patient care and developing innovative medical devices and therapy solutions.

The Job Responsibilities :

• Analyze data to identify trends and insights.
• Collaborate with product and engineering teams to define data requirements and drive data-driven decision-making.
• Design and implement data models to effectively support various product use cases.
• Create, deploy, and optimize large scale data.
• Use extensive data engineering expertise to design and build solutions / products for analyzing large data sets and identify patterns and relationships.
• Manage data sources, organize data and create data assets using identified open source or proprietary tools.
• Develop and continuously optimize data ingestion processes for improved reliability and performance.
• Establish monitoring and alerting systems to proactively identify and address potential data pipeline issues.
• Develop and maintain internal tools to streamline data access and analysis for all teams.
• Create and deliver documentation to educate product teams on data best practices and tools.
• Communicate technical concepts effectively to both technical and non-technical audiences.
• Foster a culture of sharing, reuse, design for scale stability, and operational efficiency of data and analytical solutions.
• Codify best practices for future reuse in the form of accessible, reusable patterns, templates, and code bases to facilitate data capturing and management.

Education and Experience :

Required :

• Bachelor's Degree in Data Science, Computer Science, Statistics.
• Minimum 3 years in data engineering / analytics space
• Strong problem-solving skills
• Experience in any from MS Azure, AWS, Python, Kafka, and associated cloud data platforms, cloud data warehouse technologies (Snowflake / Redshift), and Advanced Analytical platforms (e.

g., Dataiku and Databricks).

• Attention to detail and organization / documentation skills
• Ability to prioritize and triage deadline-driven tasks in a high-pressure environment
• Experience manipulating and analyzing complex, high-volume data from varying sources
• Ability to communicate complex quantitative analysis in a clear, precise, actionable manner

Preferred :

• Strong understanding of data modeling (conceptual, logical, and physical) using different data modeling methodologies and analytics concepts.
• Expertise in data integration, ETL tools, and data engineering programming / scripting languages (Python, Scala, SQL) for data preparation and analysis.
• Experience with triple stores or graph databases (e.g., GraphDB, Stardog, Jena Fuseki)
• Proficient with building domain ontologies and relevant W3C standards - RDF, RDFS, OWL, SKOS, SPARQL and associated Ontology Editors (e.

g., TopBraid Composer, Protégé).

Knowledge of data governance and compliance policies.

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