Data Science, Senior Associate

Peraton; United States; On-site; USD 80,000 - 128,000; Full time

Job summary

Peraton seeks a Data Scientist / ML Platform Engineer to contribute across the full ML development lifecycle within a HIPAA-governed, FedRAMP-compliant healthcare analytics environment.

You will build and evaluate ML models, support governance and deployment, and contribute to data engineering and platform operations in collaboration with dedicated teams.

Qualifications

• BS/BA in a relevant field required; MS/MA preferred.
• Experience with SQL and Python for ML; familiarity with ML frameworks.
• Hands-on experience with MLFlow or equivalent for experiment tracking and governance.

Responsibilities

• Develop, train, and evaluate ML models (classification, regression, clustering, anomaly detection).
• Contribute to MLOps using MLFlow for experiment tracking and deployment governance.
• Support model governance, versioning, and automated testing across ML lifecycle.
• Build production ML operations: monitoring, drift detection, alerting, incident escalation.
• Develop model serving infrastructure, feature pipelines, and lifecycle automation.
• Apply explainability techniques (SHAP/LIME) and produce documentation.
• Assist data ingestion and ELT/ETL within Spark, Snowflake/Databricks environments.

Skills

SQL

Python

MLFlow

GitHub

Spark

Databricks

Bash

Cloud

SDLC

Communication

Education

BS/BA in a related field

Tools

Databricks

Spark

Unity Catalog

MLFlow

Job description

About Peraton

Peraton is a next-generation national security company that drives missions of consequence spanning the globe and extending to the farthest reaches of the galaxy. As the world's leading mission capability integrator and transformative enterprise IT provider, we deliver trusted, highly differentiated solutions and technologies to protect our nation and allies. Peraton operates at the critical nexus between traditional and nontraditional threats across all domains: land, sea, space, air, and cyberspace. The company serves as a valued partner to essential government agencies and supports every branch of the U.S. armed forces. Each day, our employees solve the most daunting challenges that our customers face. Visit peraton.com to learn how we're keeping people around the world safe and secure.

About Peraton

Peraton is a next-generation national security company that drives missions of consequence spanning the globe and extending to the farthest reaches of the galaxy. As the world's leading mission capability integrator and transformative enterprise IT provider, we deliver trusted, highly differentiated solutions and technologies to protect our nation and allies. Peraton operates at the critical nexus between traditional and nontraditional threats across all domains: land, sea, space, air, and cyberspace. The company serves as a valued partner to essential government agencies and supports every branch of the U.S. armed forces. Each day, our employees solve the most daunting challenges that our customers face. Visit peraton.com to learn how we're keeping people around the world safe and secure.

About The Role

We are looking for a Data Scientist / ML Platform Engineer to contribute across the full ML development lifecycle - from model building and experimentation to production deployment and monitoring. Core responsibilities are in applied data science and MLOps, with secondary contributions to data engineering and light platform operations. This role works within established platform patterns alongside dedicated infrastructure engineers, without requiring their involvement for routine ML and data tasks. All work is performed in a HIPAA-governed, FedRAMP-compliant healthcare analytics environment.

What you'll do

• Develop, train, and evaluate ML models (classification, regression, clustering, anomaly detection) and contribute to LLM-based capabilities such as RAG pipelines and prompt evaluation.
• Support model governance and deployment practices using MLFlow, including experiment tracking, model versioning, registry promotion workflows, and automated testing across the ML lifecycle.
• Contribute to production ML operations: model performance monitoring, drift detection, automated alerting, and incident escalation to maintain reliability and SLA compliance.
• Build and improve model serving infrastructure, feature pipelines, and lifecycle automation to support reproducible, scalable model development and inference.
• Apply explainability techniques (e.g., SHAP, LIME) and produce technical documentation to support stakeholder transparency and compliance requirements.
• Contribute to data ingestion, ELT/ETL transformation, and pipeline reliability using Spark and SQL-based frameworks within Snowflake and Databricks environments.
• Support pipeline orchestration, medallion architecture conventions, and data stewardship practices (metadata management, PII handling, lineage tracking in Unity Catalog).
• Perform occasional system administration tasks in collaboration with platform teams, including environment configuration, access management, compute troubleshooting, and secrets handling using platform-native tools.

Qualifications

Basic Qualifications

• 2 years with BS/BA; 0 years with MS/MA; 6 years with HS Diploma/equivalent
• Demonstrated experience with SQL and Python, including Python-based ML frameworks (e.g., scikit-learn, XGBoost, PyTorch, or TensorFlow).
• Hands-on experience with MLFlow or equivalent tools for experiment tracking, model governance, and lifecycle management.
• Strong understanding of SDLC fundamentals and experience with GitHub or equivalent version control.
• Experience with distributed compute environments (e.g., Spark, Databricks) and cloud-native services.
• Basic proficiency with Bash or shell scripting for automation and environment setup.
• Ability to collaborate across multidisciplinary teams and communicate technical concepts to varied audiences.
• Ability to obtain and maintain a Public Trust clearance
• US citizenship required or Green Card holder and must have been in the USA for 3 of the last 5 years.

Preferred Qualifications:

• Experience with MLOps practices including CI/CD for ML, containerization, feature pipeline automation, and model deployment frameworks.
• Experience with Databricks E2 components (Unity Catalog, Feature Store, Delta Live Tables) and/or model serving and drift monitoring tools (e.g., Databricks Model Serving, Evidenly, etc.).
• Experience with LLM frameworks (e.g., LangChain, LlamaIndex, Hugging Face Transformers) and familiarity with model explainability libraries (e.g., SHAP, LIME).
• Advanced Spark performance optimization experience and/or API development using Databricks REST APIs.
• Experience with healthcare analytics data (preferably Medicare or Medicaid) and familiarity with HIPAA or FedRAMP compliance constraints.
• Experience building data pipelines in a Snowflake or Databricks environment.
• Familiarity with orchestration tools (Airflow, Databricks Workflows).
• Exposure to streaming data patterns using Spark Structured Streaming, Delta Live Tables, or Kafka.
• Familiarity with environment reproducibility tooling (Docker, conda) and scripting (Python, Bash) to support automation and CI/CD tasks

Details

Target Salary Range: $80,000 - $128,000. This represents the typical salary range for this position. Salary is determined by various factors, including but not limited to, the scope and responsibilities of the position, the individual's experience, education, knowledge, skills, and competencies, as well as geographic location and business and contract considerations. Depending on the position, employees may be eligible for overtime, shift differential, and a discretionary bonus in addition to base pay.

Benefits Statement: Peraton offers eligible employees a variety of benefits including medical, dental, vision, life, health savings account, short/long term disability, EAP, parental leave, 401(k), paid time off (PTO) for vacation, and company paid holidays. A full listing of available benefits can be viewed at https://www.careers.peraton.com/benefits.

EEO:Equal opportunity employer, including disability and protected veterans, or other characteristics protected by law.