Data Scientist enhancing merchandising and inventory performance using machine learning techniques at Nordstrom. Collaborating with teams to develop data - driven solutions for better customer experiences.
About the role
- Data Scientist/Machine Learning Engineer at Northrop Grumman building production-grade analytics solutions. Collaborating with stakeholders and leveraging cloud technologies for impactful data insights.
Responsibilities
- Work directly with stakeholders (engineers, program managers, subject matter experts) to scope problems, identify constraints, and iterate on technical solutions
- Bridge analytics and infrastructure by understanding both the business problem and the approach, then building systems that deliver insights
- Build user ‑ friendly, production ‑ grade ML/AI applications (e.g., Streamlit, Gradio) that provide data insights to teams across the enterprise and enable better decision making
- Develop and maintain cloud ‑ based infrastructure (AWS, Databricks) and tooling to support scalable and reliable data analytics workflows
- Design and implement CI/CD pipelines, infrastructure ‑ as ‑ code (Terraform, AWS CloudFormation), and MLOps practices that enhance team productivity
- Optimize existing workflows and advocate for software engineering best practices (version control, modular design, testing) to drive team efficiency and code quality
- Stay current on cloud technologies, MLOps trends, and application frameworks to identify opportunities for improvement
Requirements
- Must have a PhD with 4 years of relevant professional experience OR a Master’s degree with 6 years of relevant professional experience OR Bachelor’s degree with 8 years of relevant professional experience
- Must have strong proficiency with Python, SQL, and Git
- Must have experience with frameworks for rapid application development (e.g., Streamlit, Gradio, Starlette, Next.js)
- Must have knowledge of DevOps or MLOps concepts and their application in data science workflows
- Must have strong understanding of containerization (e.g., Docker, Podman)
- Must have the ability to work collaboratively with data teams (data scientists, analysts) to support analytics workflows and insights
- Must have demonstrated problem ‑ solving and critical ‑ thinking skills with an ability to handle complex technical challenges
- Must have excellent communication skills and comfort engaging with non ‑ technical stakeholders.
Benefits
- Health insurance coverage
- Life and disability insurance
- Savings plan
- Company paid holidays
- Paid time off (PTO) for vacation and/or personal business
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