Role Description SkyePoint Decisions is seeking a Cyber Hunt Team Leader to join our team supporting the Department of Education’s (DoED) Federal Student Aid (FSA) Cybersecurity and Privacy Support Services (CPSS) in Washington, DC. This is a remote position. - Leads proactive threat hunting missions and advanced analytics. - Coordinates with SOC, CTI and other business partners and government teams to identify and mitigate advanced persistent threats (APTs). - Develops threat hypotheses, detection logic, and knowledge base of IoCs. - Supports Purple Team exercises and threat emulation. Qualifications - 10+ years of cybersecurity experience. - At least one of: CISSP, GCIH, GCFA, CEH. - Experience with EDR/NDR, SIEM, MITRE ATT&CK, and threat emulation. - Strong understanding of operating systems, networking, adversary tactics, techniques, and procedures (TTPs). - Must be a U.S. citizen. - Must be able to obtain a Public Trust. Requirements - Salary Range: $100,000-$120,000 - Salary at SkyePoint is determined by various factors, including but not limited to location, work schedule, the candidate’s combination of education, knowledge, skills, competencies, and experience, as well as contract-specific affordability, market data and business considerations. Benefits - Certification incentive program. - PTO and floating federal holiday options. - Several insurance options including HMO and High Deductible plans with Health Savings Accounts [HSAs]. - Flex Spending Accounts [FSAs]. - Full Dental Plans and Vision. - Short-Term/Long-Term Disability and Life Insurance. - 401k matched. - Flexible Work Environment.

• New logo quota in your assigned territory — full cycle from prospect to close, with meaningful self-sourced pipeline expected alongside BDR-sourced opportunities. • Named account book — build real account plans, expand into additional modules, users, sites, and geographies, and run multi-year renewal and expansion motions. • Executive engagement — Director and VP-level conversations are the default, not the exception. You'll be expected to build and defend executive relationships inside your top accounts. • Forecast discipline — accurate Salesforce hygiene, weekly pipeline reviews, and MEDDPICC-quality qualification on every deal above threshold. • Commercial negotiation — pricing, terms, multi-year structures, and discount governance within company guidelines. • Territory leadership — you run targeted campaigns, ABM plays, and field activity inside your patch. You are the CEO of your territory.

• Take full ownership of evolving and maintaining GFiber TPRM processes to optimize our existing tooling platform. Translate complex technical and non-technical risks into actionable insights for diverse stakeholders. • Identify and execute tactical opportunities to automate GRC workflows using an AI-native approach. • Apply key cybersecurity frameworks, specifically ISO 27001 and NIST CSF, to manage and mature our risk posture. Act as a proactive project driver by tracking technical inquiries and moving initiatives forward without waiting for direction. • Draft clear and effective risk presentations for senior leadership and C-suite executives. • Support M&A and corporate carve-out initiatives by aligning GRC processes with our new operational reality.

• Analyze Censys telemetry and derived datasets to identify signals that improve AI/ML model training for classification that affects security outcomes • Build and improve training and evaluation datasets using Internet telemetry, manually curated labels, and analyst-reviewed data • Drive feature discovery, feature selection, and labelling strategies for models that classify entities as benign, suspicious, or malicious • Work on multi-layer labeling and classification problems, where categories such as device type, router, honeypot, or edge service may need to be identified before risk classification • Partner with Research / Detection teams to translate security domain expertise into actionable workflows • Collaborate with ML engineers and software engineers to ensure features, labels, and model inputs are practical to productionize • Contribute to feedback loops and evaluation frameworks that improve precision, recall, confidence, and coverage over time • Build tooling to support the efforts listed above