Peraton Logo

Peraton

Data Science, Senior Associate

Posted 2 Days Ago
Be an Early Applicant
Remote
Hiring Remotely in United States
80K-128K Annually
Senior level
Remote
Hiring Remotely in United States
80K-128K Annually
Senior level
Develop and deploy machine learning models across the full lifecycle, including experimentation, MLOps, monitoring, governance, explainability, and production serving. Build data pipelines using Spark, SQL, Snowflake, and Databricks, while supporting orchestration, stewardship, compliance, and occasional platform administration. Contribute to LLM capabilities, model reliability, CI/CD, and scalable analytics in a HIPAA-governed, FedRAMP-compliant environment.
The summary above was generated by AI
Responsibilities

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
Peraton Overview

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 do the can’t be done by solving the most daunting challenges facing our customers. Visit peraton.com to learn how we’re keeping people around the world safe and secure.

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

Similar Jobs

Senior level
Financial Services
Lead measurement and analytics for onboarding and engagement marketing: design experiments (A/B and incrementality), build reusable data products and pipelines, translate business questions into rigorous analyses, identify measurement gaps, present recommendations to stakeholders, and partner with Data & Analytics and business teams to improve targeting and customer engagement.
Top Skills: Claude CodeCortexGithub CopilotPythonRSQLTableau
54 Minutes Ago
In-Office or Remote
Senior level
Senior level
Artificial Intelligence • Fintech • Software • Financial Services
Own enterprise new-logo acquisition and expansion while personally closing complex, high-value deals and carrying an individual quota. Hire, coach, and develop Enterprise AEs and SDRs; establish forecasting, pipeline, conversion, and sales operating cadences. Partner with Marketing, Product, Customer Success, Partnerships, Legal, and Finance, while presenting performance and strategic recommendations to executives and the board.
Top Skills: ChallengerChorusCommand Of The MessageForce ManagementGongHubspotLinkedin Sales NavigatorMeddpiccOutreachSalesloftZoominfo
54 Minutes Ago
In-Office or Remote
Mid level
Mid level
Artificial Intelligence • Fintech • Software • Financial Services
Own vulnerability management across endpoints, servers, and cloud infrastructure; prioritize remediation and track SLA performance. Harden AWS environments, improve identity management, investigate cloud alerts, and support application security through SAST, DAST, dependency scanning, secure code reviews, and threat modeling. Resolve security tickets, document incidents and remediation, and lead security initiatives while collaborating with engineering, IT, and compliance.
Top Skills: AWSAws ConfigBashCloudtrailDastGuarddutyIamJIRALinearOwasp Top 10PythonQualysS3SastScaSecurity HubSnykSoc 2TenableVpcWiz

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account