Data Science Architect

Job Description

All the relevant skills, qualifications and experience that a successful applicant will need are listed in the following description.

The Data Science Solutions Architect will play a critical role on our Data Science team; focusing on the design, prototype, and architecture of various data science and data products that will live on our Machine Learning Operations (MLOps) platform.

This role demands a unique blend of cloud architecture expertise, data and AI / ML knowledge, and leadership skills to successfully deliver enterprise production solutions.

Key Responsibilities

• ARCHITECTURAL DESIGN & LEADERSHIP : Design, prototype and implement scalable, reliable, and efficient Data Science products (including data architectures and pipelines to support advanced analytics and machine learning models) in collaboration with Data Scientists and stakeholders.
• SOLUTION DEVELOPMENT : Collaborate with stakeholders to understand business requirements, translating them into data science solutions that drive business value.
• TECHNOLOGY EVALUATION : Evaluate and recommend tools, technologies, and platforms to enhance data processing, storage, and machine learning capabilities in alignment with both in-flight and future MLOPS platform roadmap and Responsible AI requirements.
• INTEGRATION : Ensure seamless integration of data science solutions with existing systems, databases, and applications.
• BEST PRACTICES : Develop and enforce best practices for data management, analysis, and modeling; ensuring high-quality, reproducible, and maintainable solutions.
• CROSS-FUNCTIONAL COLLABORATION : Work closely with data scientists, data engineers, machine learning engineers, software developers, cloud engineers, product managers, and business analysts to deliver end-to-end solutions that are aligned with organizational objectives.
• DOCUMENTATION : Create comprehensive documentation of data architectures, solution designs, and implementation processes.
• MONITORING & PERFORMANCE OPTIMIZATION : Continuously monitor and optimize data pipelines and models for performance and scalability;

taking into account explainability, data drift detection, and fairness metrics.

• INNOVATION : Stay current with industry trends, emerging technologies, and best practices in data science and analytics.
• Performs other duties as assigned.
• Practices and adheres to the "Code of Conduct" philosophy and "Mission and Value Statement." Typical workweek hours can vary depending on workload and project deliverables.

Education & Experience

• Bachelor Degree
• Masters / PhD Degree

Knowledge, Skills, Abilities, Behaviors :

REQUIREMENTS

• 6+ years of overall experience in the technology or data field with demonstrated progressive responsibilities, particularly in data and AI / ML-related work.
• Proficient in engineering and coding skills in Python and SQL.
• Expertise in cloud solutions is essential.
• Strong background in AI / ML or Data Sciences technologies and delivery.
• Great multi-disciplinary knowledge of technology space (data, cloud, UI, security).
• Excellent communication, leadership, and project management skills.
• Healthcare domain knowledge and experience.
• Experience in Google Cloud Platform (GCP).
• Experience designing cloud solutions for streaming and batch data science work.

Travel Required

Qualifications :

All your information will be kept confidential according to EEO guidelines.

J-18808-Ljbffr