Enhance Our Capabilities Jobs in Washington DC

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Senior Associate, Data Science - People Analytics

Company: Capital One

Location: Washington DC

Posted Mar 01, 2025

Capital One is seeking a Senior Associate Data Science specialist for their People Strategy & Analytics team. The role involves applying data science and machine learning to understand associate behavior and inform talent strategies. The ideal candidate should be passionate about human capital, innovative, creative, technically skilled, and statistically minded. They should have a degree in a quantitative field and experience in data analysis, open-source programming, machine learning, and relational databases. Preferred qualifications include a master's degree in a STEM field, AWS experience, and proficiency in Python, PyTorch, Scala, or R.

Frequently Asked Questions

Typical salary ranges by seniority
Entry‑level (0‑2 yrs) starts at $90‑$110k, mid‑level (2‑5 yrs) $110‑$140k, senior (5‑10 yrs) $140‑$170k, principal/lead >$170k. These ranges reflect roles like Platform Enablement Engineer, Data Ops Lead, and AI Capability Architect.
Required skills and certifications
Core competencies include Kubernetes, Terraform, Python, CI/CD (GitHub Actions, GitLab), and cloud expertise (AWS Certified Solutions Architect – Associate/Professional, Azure Fundamentals). Advanced roles demand knowledge of Data Mesh, ML Ops frameworks, and security best practices.
Remote work availability
Over 80% of Enhance Our Capabilities listings permit fully remote or hybrid arrangements. Companies prioritize distributed teams and provide VPN, cloud dev environments, and asynchronous communication tools.
Career progression paths
Typical ladder moves from Platform Engineer → Senior Engineer → Lead Engineer → Principal Engineer → Technical Fellow. Parallel tracks include Product Enablement Lead or Data Ops Lead, each with cross‑functional responsibilities.
Industry trends for Enhance Our Capabilities
Key trends are the rise of serverless event‑driven architectures, increased use of GitOps for infrastructure, and the convergence of AI with DevOps (MLOps). Organizations are investing in low‑code platform enablement to speed innovation.

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