Data Scientist -3

Realign Llc; Seattle (WA); On-site; USD 120,000 - 180,000; Full time

Job summary

Realign Llc is seeking a Data Scientist specializing in Supply Chain Analytics to drive MRO process optimization and supply chain insights in Seattle, WA. The role requires strong AWS and ML skills, data modeling, NLP, and GenAI experience.

You will develop scalable data models, validate models, and publish performance metrics while ensuring secure, auditable deployments. You will collaborate with stakeholders across procurement, inventory and logistics to translate data into actionable

Qualifications

• Proficiency in AWS services, AI/ML modeling, data modeling, data engineering, data analytics, Tableau and Azure DevOps for project management.
• Strong proficiency in Python and/or other programming language.
• Perform data analysis to identify trends and bottlenecks in MRO process and supply chain.
• Experience with unstructured data processing and NLP.
• Experience with generative AI and agentic AI frameworks.
• Apply analytics to business problems and develop, test and validate ML models from historical data.
• Develop data models using AWS services (SageMaker, Glue, Lambda, S3, Redshift).
• Publish model metrics (accuracy, precision, recall, F1, MSE, R^2).
• Configure monitoring/logging/alerts (CloudWatch, SNS).
• Develop modular, secure code passing Info-sec scans.
• Automate deployments and infrastructure changes.
• Document runbooks for models and cloud assets.
• Conduct testing/validation of data and models.

Responsibilities

• Collaborate with stakeholders to understand current MRO process flow.
• Gather insights on process flow and supply chain for maintenance, repair and overhaul operations.
• Analyze data to optimize quality and speed of services.
• Incorporate models into broader applications to drive actions by business/ops.
• Develop and validate ML models.
• Create data ingestion patterns on AWS and make outputs consumable.
• Ensure security, governance and monitoring per ARB guidelines.
• Handover documentation with training and runbooks.

Skills

AWS services

AI/ML modeling

Data modeling

Data engineering

Data analytics

Tableau

Azure DevOps

Python

Project management

Data analysis

NLP

GenAI frameworks

Business analytics

ML modeling

Model evaluation

Monitoring

Secure coding

Automation

Runbook documentation

Testing

Tools

SageMaker

Glue

Lambda

S3

Redshift

CloudWatch

SNS

Tableau

Azure DevOps

Python

Job description

Seattle, Washington 98039 Posted October 2nd, 2026

Job Title: Data Scientist - Supply Chain Analytics

Location: Seattle, WA

Full Time

Job Description

Must Have Technical/Functional Skills

• Proficiency in AWS services, AI/ML modeling, Data modeling, data engineering, data analytics, tableau and Azure devops for project management.
• Strong Proficiency in Python and/or other programming language
• Should perform data analysis detailing the trends and bottlenecks in the MRO process and part supply chain.
• Experience with unstructured data processing and NLP
• Experience with generative-ai and agentic AI frameworks
• Experience in applying analytics in business problems
• Should develop, test, and validate the various machine learning models to predict for issues for future operations based on the historical data analysis from past operations.
• Development of data models using AWS services (e.g., Sagemaker, Glue, Lambda, S3, Redshift).
• Publish accuracy, precision, recall, F1-Score, MSE, R-squared etc. for the models
• Configuration of monitoring, logging, and alerting mechanisms (e.g., CloudWatch, SNS).
• Develop modular code that passes the static and dynamic Info-sec vulnerability scans
• Deploy automation to change the solution to be automated. E.g. Deployments, Certificate updates, Infrastructure changes, code changes, failure notifications etc.
• Document Runbook details of the above-mentioned models along with all the cloud and code assets created by the team.
• Conduct testing and validation activities for data and developed models.

Supply Chain Domain Knowledge:

Strong grasp of supply chain processes, including inventory management, procurement and logistics.

• Collaborate with stakeholders to understand the current MRO process flow
• Gather actionable insights into the process flow and supply chain for the maintenance, repair, and overhaul operations
• Analyze data around these processes and identify places where they can be optimized to provide quality services with greater speed.
• Incorporated models into a broader application which will drive actions by business and operations stakeholders
• Algorithmic framework to process financial data and generate structured reports
• Validate accuracy of the generated reports against human written reports
• Algorithmic framework to process and derive insights from unstructured constraint notes data
• Identify data trends such as last time buyer updated the record and other informatio n to identify potentially stale, complete, cancelled and/or erroneous records
• Development of the project plan with key milestones and project deliverables
• Report out to stakeholders highlighting achievements, risks, and future work.
• Develop, test, and validate the various machine learning models
• Follow the Agile standard for the development of the requested proposal.
• Bring best practices, standards, and innovative ideas for Data Science, process, architecture, and design.
• Requirements gathering and architecture design.
• Development of data models using AWS services (e.g., Sagemaker, Glue, Lambda, S3, Redshift).
• Develop new Data Ingestion Patterns, use existing patterns/frameworks.
• Make data model outputs available for consumption, applications, and self-service.
• Build models that are performant and optimized for cloud expenses.
• Implement security, governance, monitoring, alerting, and job orchestration as defined by ARB.
• Conduct reviews along with frequent communication for stakeholders.
• Deployment of ingestion pipelines into dev, pre, and production environments.
• Configuration of monitoring, logging, and alerting mechanisms (e.g., CloudWatch, SNS).
• Unit testing, integration testing, functional, and non-functional testing.
• Handover documentation with a training session.

Roles & Responsibilities

• Collaborate with stakeholders to understand the current MRO process flow
• Gather actionable insights into the process flow and supply chain for the maintenance, repair, and overhaul operations
• Analyze data around these processes and identify places where they can be optimized to provide quality services with greater speed.
• Incorporated models into a broader application which will drive actions by business and operations stakeholders
• Modeling & Advanced Analytics
• Algorithmic framework to process financial data and generate structured reports
• Validate accuracy of the generated reports against human written reports
• NLP/GenAI Modeling
• Algorithmic framework to process and derive insights from unstructured constraint notes data
• Identify data trends such as last time buyer updated the record and other informatio n to identify potentially stale, complete, cancelled and/or erroneous records
• Development of the project plan with key milestones and project deliverables
• Report out to stakeholders highlighting achievements, risks, and future work.
• Develop, test, and validate the various machine learning models
• Follow the Agile standard for the development of the requested proposal.
• Bring best practices, standards, and innovative ideas for Data Science, process, architecture, and design.
• Requirements gathering and architecture design.
• Development of data models using AWS services (e.g., Sagemaker, Glue, Lambda, S3, Redshift).
• Develop new Data Ingestion Patterns, use existing patterns/frameworks.
• Make data model outputs available for consumption, applications, and self-service.
• Build models that are performant and optimized for cloud expenses.
• Implement security, governance, monitoring, alerting, and job orchestration as defined by ARB.
• Conduct reviews along with frequent communication for stakeholders.
• Deployment of ingestion pipelines into dev, pre, and production environments.
• Configuration of monitoring, logging, and alerting mechanisms (e.g., CloudWatch, SNS).
• Unit testing, integration testing, functional, and non-functional testing.
• Handover documentation with a training session.

Generic Managerial Skills, If any

• Exceptional communication to bridge technical and non-technical teams.
• Strong analytical and problem-solving skills.
• Stakeholder management and cross-functional collaboration.

Required Skills

Job Type: Full Time

Job Category: IT

Job Description

Job Title: Data Scientist - Supply Chain Analytics

Location: Seattle, WA

Full Time

Job Description

Must Have Technical/Functional Skills

• Proficiency in AWS services, AI/ML modeling, Data modeling, data engineering, data analytics, tableau and Azure devops for project management.
• Strong Proficiency in Python and/or other programming language
• Should perform data analysis detailing the trends and bottlenecks in the MRO process and part supply chain.
• Experience with unstructured data processing and NLP
• Experience with generative-ai and agentic AI frameworks
• Experience in applying analytics in business problems
• Should develop, test, and validate the various machine learning models to predict for issues for future operations based on the historical data analysis from past operations.
• Development of data models using AWS services (e.g., Sagemaker, Glue, Lambda, S3, Redshift).
• Publish accuracy, precision, recall, F1-Score, MSE, R-squared etc. for the models
• Configuration of monitoring, logging, and alerting mechanisms (e.g., CloudWatch, SNS).
• Develop modular code that passes the static and dynamic Info-sec vulnerability scans
• Deploy automation to change the solution to be automated. E.g. Deployments, Certificate updates, Infrastructure changes, code changes, failure notifications etc.
• Document Runbook details of the above-mentioned models along with all the cloud and code assets created by the team.
• Conduct testing and validation activities for data and developed models.

Supply Chain Domain Knowledge:

Strong grasp of supply chain processes, including inventory management, procurement and logistics.

Roles & Responsibilities

• Collaborate with stakeholders to understand the current MRO process flow
• Gather actionable insights into the process flow and supply chain for the maintenance, repair, and overhaul operations
• Analyze data around these processes and identify places where they can be optimized to provide quality services with greater speed.
• Incorporated models into a broader application which will drive actions by business and operations stakeholders
• Modeling & Advanced Analytics
• Algorithmic framework to process financial data and generate structured reports
• Validate accuracy of the generated reports against human written reports
• NLP/GenAI Modeling
• Algorithmic framework to process and derive insights from unstructured constraint notes data
• Identify data trends such as last time buyer updated the record and other informatio n to identify potentially stale, complete, cancelled and/or erroneous records
• Development of the project plan with key milestones and project deliverables
• Report out to stakeholders highlighting achievements, risks, and future work.
• Develop, test, and validate the various machine learning models
• Follow the Agile standard for the development of the requested proposal.
• Bring best practices, standards, and innovative ideas for Data Science, process, architecture, and design.
• Requirements gathering and architecture design.
• Development of data models using AWS services (e.g., Sagemaker, Glue, Lambda, S3, Redshift).
• Develop new Data Ingestion Patterns, use existing patterns/frameworks.
• Make data model outputs available for consumption, applications, and self-service.
• Build models that are performant and optimized for cloud expenses.
• Implement security, governance, monitoring, alerting, and job orchestration as defined by ARB.
• Conduct reviews along with frequent communication for stakeholders.
• Deployment of ingestion pipelines into dev, pre, and production environments.
• Configuration of monitoring, logging, and alerting mechanisms (e.g., CloudWatch, SNS).
• Unit testing, integration testing, functional, and non-functional testing.
• Handover documentation with a training session.

Generic Managerial Skills, If any

• Azure devops for project management
• Exceptional communication to bridge technical and non-technical teams.
• Strong analytical and problem-solving skills.
• Stakeholder management and cross-functional collaboration.

Required Skills

Data Analyst