21 hours ago

Data Scientist

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 17 hours agoStatus: Live

Reposted: first listed 1 week ago

Job Summary

Architect data models and an intelligence layer that enable AI agents to automate business processes across the product ecosystem. Build and deploy machine learning models using AWS SageMaker and MLOps practices, while creating reliable pipelines and zero-copy data federation between Snowflake/AWS and enterprise CRM systems. Translate complex outputs into production-ready data products for reports and dashboards, and communicate data and architecture decisions to technical and non-technical stakeholders.

Location: Canada, United States

Workplace: Remote

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Design relational, dimensional, and analytical data models from large, disparate datasets and extend them into Salesforce Data 360 for downstream analytics and Agentforce AI agents.
•Partner with Data Engineering and Salesforce teams to define data requirements, ensure pipeline integrity, design schemas, and operationalize data flows including zero-copy data federation between Snowflake/AWS and CRM systems.
•Design, build, train, and validate machine learning models, packaging, deploying, and monitoring them efficiently in production at scale.
•Convert model outputs into production-ready data products and structured data views, communicating data modeling and architecture decisions to technical and non-technical stakeholders.
•Develop underlying data layers, views, and infrastructure that power reports and dashboards with aggregate (industry trends) and per-customer insights.

Pay and Benefits

Salary: USD 120,000 - 150,000 annually

Key Requirements

•4+ years of hands-on experience in data science or data engineering, including developing data models and deploying ML infrastructure in production.
•Strong Python proficiency for heavy data manipulation, ETL/ELT, and system integration.
•Hands-on experience building and deploying ML models with AWS SageMaker and automated deployment workflows.
•Advanced SQL skills plus data warehousing, dimensional modeling (e.g., Kimball paradigms), and schema/database design for ML pipelines.
•Bachelor’s degree in a technical field such as Computer Science, Software Engineering, Information Systems, or a related quantitative discipline.

Experience:4+ yearsData scienceData engineeringMLMLOpsSaaSNon-profit softwareSocial good

Education:Bachelor's

Skills:AutonomousCommunicationSelf-startingStakeholder communication

Tech Stack:PythonSQLETLELTAWSSnowflakeAWS SageMakerMLOpsSalesforce Data 360Salesforce Data CloudAgentforceZero-copy data federationDimensional modelingKimball paradigmsSnowparkStreamsTasksMulesoftNLPLLMs

Company Brief

Zipline

Provides talent acquisition software and recruiting workflow tools for hiring teams. The platform appears focused on helping organizations source, track, and manage candidates more efficiently.

Industry: HR Tech

Website

Loading job details...

Preparing the role view and application actions.

Zipline

21 hours ago

Data Scientist

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 17 hours agoStatus: Live

Reposted: first listed 1 week ago

Job Summary

Location: Canada, United States

Workplace: Remote

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Design relational, dimensional, and analytical data models from large, disparate datasets and extend them into Salesforce Data 360 for downstream analytics and Agentforce AI agents.
•Partner with Data Engineering and Salesforce teams to define data requirements, ensure pipeline integrity, design schemas, and operationalize data flows including zero-copy data federation between Snowflake/AWS and CRM systems.
•Design, build, train, and validate machine learning models, packaging, deploying, and monitoring them efficiently in production at scale.
•Convert model outputs into production-ready data products and structured data views, communicating data modeling and architecture decisions to technical and non-technical stakeholders.
•Develop underlying data layers, views, and infrastructure that power reports and dashboards with aggregate (industry trends) and per-customer insights.

Pay and Benefits

Salary: USD 120,000 - 150,000 annually

Key Requirements

•4+ years of hands-on experience in data science or data engineering, including developing data models and deploying ML infrastructure in production.
•Strong Python proficiency for heavy data manipulation, ETL/ELT, and system integration.
•Hands-on experience building and deploying ML models with AWS SageMaker and automated deployment workflows.
•Advanced SQL skills plus data warehousing, dimensional modeling (e.g., Kimball paradigms), and schema/database design for ML pipelines.
•Bachelor’s degree in a technical field such as Computer Science, Software Engineering, Information Systems, or a related quantitative discipline.

Experience:4+ yearsData scienceData engineeringMLMLOpsSaaSNon-profit softwareSocial good

Education:Bachelor's

Skills:AutonomousCommunicationSelf-startingStakeholder communication

Company Brief

Zipline

Provides talent acquisition software and recruiting workflow tools for hiring teams. The platform appears focused on helping organizations source, track, and manage candidates more efficiently.

Industry: HR Tech

Website