Environmental Data Manager
Leidos
ETLSQL
Senior Data Scientist – AI, Strategy
Red Nucleus
full-time
Posted on:
Location Type: Remote
Location: Remote • 🇺🇸 United States
Visit company websiteJob Level
Senior
Tech Stack
AWSAzureCloudPythonPyTorchScikit-LearnTensorflow
About the role
- Identify high-impact opportunities for AI and advanced analytics to create new product capabilities
- Contribute to the design and evolution of data products, from early prototype to full-scale deployment (build in collaboration with a broader team, either internal or external)
- Help develop frameworks for data solution productization, ensuring repeatability, governance, and ease of adoption
- Design and build machine learning models and algorithms that solve core business challenges
- Translate models into production-ready, reusable components that can be deployed at scale across business units for both internal and client use
- Collaborate with BUs and other data scientists / engineers (internal or outsourced) to package, deploy, and maintain data products and services that drive efficiency and innovation
- Support the development of intelligent tools and platforms that can be scaled across multiple use cases
- Engage in product thinking (through workshops and other forums) to ensure data solutions are user-friendly, modular, and aligned with business needs
- Collaborate with business units to turn insights into actionable, productized outputs
- Support BUs in conducting deep-dive analyses to uncover meaningful insights from structured and unstructured data
- Visualize and communicate findings in a clear, business-relevant narrative that informs decision-making
- Ensure all data solutions are developed with privacy and compliance requirements in mind
- Document data model and product assumptions, methodologies, and limitations to support responsible use and ongoing maintenance
Requirements
- Bachelor's or Master’s degree in Data Science, Computer Science, Engineering, or a related field
- 3-10 years of experience in data science, analytics, or applied machine learning
- Strong programming skills in various languages (for example: python, R, etc, with broad experience in libraries (for example: such as scikit-learn, TensorFlow, or PyTorch)
- Proficient in working with cloud-based data platforms (for example: Snowflake, AWS, Azure, Databricks)
- Hands-on experience operationalizing models or data pipelines in production environments
- Solid understanding of statistics, machine learning, and model performance evaluation
- Experience developing or contributing to data products or AI-powered tools preferred
Benefits
- Meaningful work
- True sense of community
- Fun work environment
- Celebration of achievements
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
machine learningdata scienceanalyticsprogrammingstatisticsmodel performance evaluationdata product developmentdata pipelinesAI-powered toolsdata solution productization
Soft skills
collaborationcommunicationproduct thinkinganalytical thinkinguser-friendly designinsight generationdocumentationgovernanceinnovationadaptability
Certifications
Bachelor's degree in Data ScienceMaster’s degree in Data ScienceBachelor's degree in Computer ScienceMaster’s degree in Computer ScienceBachelor's degree in EngineeringMaster’s degree in Engineering
