Data Scientist – Snowflake Cortex AI / Snowpark ML

Peer Consulting Resources Inc.; Indianapolis (IN); On-site; USD 120,000 - 160,000; Full time

Job summary

Peer Consulting Resources Inc. is seeking an experienced Data Scientist to establish and expand AI capabilities within a secure Snowflake environment.

The role designs and productionizes Snowpark ML and Cortex AI workloads, ensuring data stays within the accredited boundary and governance is applied throughout the ML lifecycle.

Qualifications

• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Machine Learning, or related discipline.
• 6+ years of applied data science or machine learning experience.
• Experience deploying ML models in production.
• Hands-on experience with Snowflake Cortex AI and/or Snowpark ML.
• Strong Python and SQL programming skills.
• Experience building end-to-end ML pipelines using data housed in Snowflake.
• Understanding of FedRAMP and FISMA governance and data-security requirements.
• Experience operating in regulated or security-controlled environments.
• Experience with Amazon S3 External Stages and secure AWS-to-Snowflake data movement.
• Knowledge of AWS KMS encryption and high-volume Snowflake ingestion patterns.
• Understanding MuleSoft data-consumption and integration architectures.
• Ability to clearly document model design, assumptions, limitations, performance, and governance controls.

Responsibilities

• Design, develop, and deploy Snowpark ML and Cortex AI workloads for predictive analytics and intelligent automation.
• Ensure AI workloads stay within the governed Snowflake environment.
• Build production-ready ML pipelines using Python, SQL, Snowpark ML, and Cortex AI.
• Collaborate with DBAs and Data Engineers to ensure data quality for ML pipelines.
• Support AI deliverables during Build and Scale phases.
• Document model architecture, methodology, and governance for client review.

Skills

Data science

Machine learning

Python

SQL

Snowflake Cortex AI

Snowpark ML

FedRAMP / FISMA

Regulated environments

AWS S3 External Stages

AWS KMS

MuleSoft

Documentation

Education

Bachelor’s or Master’s degree in Data Science / CS / Stats / ML

Tools

Snowflake Cortex AI

Snowpark ML

Python

SQL

AWS S3

AWS KMS

MuleSoft

Job description

Job Title: Data Scientist – Snowflake Cortex AI / Snowpark ML

We are seeking an experienced Data Scientist to establish and expand our client’s AI and automation readiness capabilities within a secure, governed Snowflake environment.

This role will design and productionize Snowpark ML and Snowflake Cortex AI workloads that execute entirely within the client’s accredited environment. The ideal candidate brings strong applied machine learning experience, hands-on Snowflake AI expertise, and an understanding of federal security and governance requirements, including FedRAMP and FISMA.

Key Responsibilities:

• Design, develop, and deploy Snowpark ML and Snowflake Cortex AI workloads supporting predictive analytics and intelligent automation use cases.
• Ensure all AI and machine learning workloads execute within the governed Snowflake environment without moving sensitive data outside the accredited boundary.
• Build production-ready ML pipelines using Python, SQL, Snowpark ML, and Cortex AI.
• Partner with Database Architects and Data Engineers to ensure governed, reliable, and high-quality data is available for AI and ML pipelines.
• Support AI use-case execution and readiness deliverables during the Build phase (Weeks 9–26), followed by capability expansion during the Scale phase.
• Document model architecture, methodology, assumptions, limitations, performance metrics, and validation results for client review and Contracting Officer’s Representative (COR) acceptance.
• Advise the Engagement Lead and IT Business Analyst on the feasibility, value, security implications, and prioritization of AI-enabled use cases.
• Design secure ingestion patterns using Amazon S3 External Stages and AWS-to-Snowflake data movement.
• Apply AWS KMS encryption and Snowflake security controls to protect regulated data.
• Support high-volume Snowflake ingestion and processing patterns.
• Collaborate with integration teams supporting MuleSoft data consumption and integration architectures.
• Incorporate AI governance, explainability, traceability, monitoring, and auditability into the ML lifecycle.

Required Qualifications:

• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Machine Learning, or a related discipline.
• At least 6 years of applied data science or machine learning experience.
• Demonstrated experience deploying and supporting machine learning models in production.
• Hands‑on experience with Snowflake Cortex AI and/or Snowpark ML.
• Strong programming experience with Python and SQL.
• Experience building end‑to‑end machine learning pipelines using data housed in Snowflake.
• Understanding of federal AI governance and data‑security requirements, including FedRAMP and FISMA.
• Experience operating within regulated, accredited, or security‑controlled environments.
• Experience with Amazon S3 External Stages and secure AWS‑to‑Snowflake data movement.
• Knowledge of AWS KMS encryption and high‑volume Snowflake ingestion patterns.
• Understanding of MuleSoft data‑consumption and integration architectures.
• Ability to clearly document model design, assumptions, limitations, performance, and governance controls for technical and government stakeholders.

Preferred Qualifications:

• Experience productionizing AI or machine learning solutions within a federal, state, local government, or similarly regulated environment.
• Experience supporting formal client review, compliance assessment, or COR acceptance processes.
• Familiarity with responsible AI practices, model‑risk management, explainability, performance monitoring, and audit documentation.
• Experience translating business requirements into secure and practical AI‑enabled use cases.