Challenging Opportunities For You To Learn And Grow Professionally Jobs in Washington DC

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Looking for Challenging Opportunities For You To Learn And Grow Professionally jobs in Washington DC? Browse our curated listings with transparent salary information to find the perfect Challenging Opportunities For You To Learn And Grow Professionally position in the Washington DC area.

Manager, Product Management - Fraud (US Card)

Company: Capital One

Location: Washington DC

Posted Feb 01, 2025

Capital One's Fraud Product team is seeking a Product Manager for two key areas: Authentication & Verification and Payment Fraud Decisioning. The role involves driving the roadmap and delivery for real-time intelligent authentication experiences, determining strategy for pooling and reusing authentication tools, building a 101 Learning of the Authentication and Verification Space, outlining CX pain points, and managing a Senior Associate. The Product Manager will also lead a tech team, own feature and capability delivery, partner with data science teams, and collaborate with partner teams. Key qualifications include intellectual curiosity, communication and influencing skills, being a doer, passionate and customer-focused, a learner, and a team player. Basic qualifications include a Bachelor's Degree or military experience and at least 3 years of product management experience or experience in product design, agile delivery, business analysis, data science, or software engineering.

Principal Associate, Security Intelligence Analyst

Company: Capital One

Location: Washington DC

Posted Feb 01, 2025

Capital One's Global Workplace Services GWS team is seeking a Principal Associate Security Intelligence Analyst. The role involves collecting, analyzing, and interpreting security risk intelligence information to support the Protective Intelligence program. Responsibilities include providing near real-time intelligence support, conducting comprehensive risk assessments, and contributing to the production of intelligence products. The ideal candidate will have a high level of skill in OSINT techniques, experience in intelligence analysis, and the ability to work independently and proactively. The role requires at least 3 years of experience in intelligence gathering, intelligence database search tools, intelligence analysis, or a combination of the three, and at least 3 years of experience with open source intelligence data collection, data mining, and investigative techniques. The minimum annual salary for this role is $102,700 in McLean, VA.

Frequently Asked Questions

What are typical salary ranges by seniority in these challenging roles?
Junior AI/ML Engineers earn $90k–$110k, mid‑level $120k–$150k, senior $160k–$200k. Cloud Architects start at $110k–$140k, rise to $170k–$210k for senior architects, and can exceed $250k for principal roles. DevOps and Cybersecurity positions follow similar tiered ranges, with senior analysts earning $140k–$180k and experts over $200k.
Which skills and certifications are most demanded?
Core skills include Python, SQL, and version control. AI roles require TensorFlow, PyTorch, and Jupyter. Cloud positions demand AWS Certified Solutions Architect, GCP Professional Cloud Architect, or Azure Solutions Architect Expert, plus Terraform and Kubernetes. Cybersecurity roles favor CISSP, CISM, or CompTIA Security+ and hands‑on experience with SIEM tools like Splunk.
Is remote work available in these positions?
Approximately 70% of the listed roles support full‑remote or hybrid arrangements. Cloud and DevOps offers often allow work-from‑anywhere, while on‑site requirements are rare for AI/ML and data engineering, especially in companies emphasizing agility.
What career progression paths exist?
Typical ladders start at junior engineer → mid‑level → senior → tech lead → principal engineer → engineering manager or VP of Engineering. For cybersecurity, the path is analyst → senior analyst → lead analyst → security manager. Continuous learning and certifications accelerate movement up these tracks.
What industry trends shape these challenging opportunities?
Key trends include AI democratization through AutoML platforms, edge computing for low‑latency inference, cloud‑native security models, and data privacy regulations (GDPR, CCPA). Companies invest heavily in building resilient, scalable infrastructures that integrate AI, data, and security, driving demand for multi‑disciplinary talent.

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