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Senior SOC Analyst

Location: London
Working Pattern: 4 days onsite, 1 day remote
Hours: Monday-Friday, standard business hours (no shift work)

Overview

We are seeking an experienced Senior SOC Analyst to support a major cyber security transformation programme within a global enterprise environment.

This role is ideal for a senior, hands-on Security Operations professional who combines strong incident investigation and threat analysis skills with experience in detection engineering, operational process development, and stakeholder engagement.

Working as a key bridge between regional and global Security Operations teams, you will play a critical role in the globalisation of security monitoring capabilities, helping to onboard, validate, optimise, and operationalise detection content while ensuring analysts have effective procedures and playbooks in place.

Key Responsibilities

Detection Rule Globalisation

Lead the onboarding of EMEA detection rules into the Global Security Operations Centre.Review and validate detection logic, thresholds, alert conditions and expected behaviours across SIEM platforms such as Microsoft Sentinel, Splunk, QRadar, ArcSight, Exabeam, and LogRhythm.Ensure accurate mapping of detection content to recognised threat frameworks, including MITRE ATT&CK.Identify detection gaps, duplicate content and optimisation opportunities through detection engineering, threat hunting, and alert tuning activities.Support standardisation of monitoring capabilities across global security teams covering EDR, XDR, cloud, identity, email, and network security telemetry.

SOP Development & Operationalisation

Develop and maintain Standard Operating Procedures (SOPs) for Tier 1 and Tier 2 SOC teams.Create investigation workflows, triage processes and escalation procedures for security incidents across Microsoft Defender, CrowdStrike, Cortex XDR, SentinelOne, Carbon Black, Azure, AWS, and GCP environments.Define required enrichment data, threat intelligence inputs and decision-making criteria.Ensure procedures are practical, repeatable and aligned with global security operations.Develop analyst playbooks and support SOAR and automation initiatives using technologies such as Microsoft Sentinel Automation, Cortex XSOAR, Splunk SOAR, Tines, and Swimlane.

Threat Analysis & Detection Validation

Validate the effectiveness of security detections through threat-focused analysis and threat hunting activities.Perform quality assurance reviews of detection rules and analyst handling processes.Review and simulate alert scenarios to confirm investigation workflows and expected outcomes.Analyse attacker tactics, techniques and procedures (TTPs) and ensure detection content remains aligned with emerging threats.Utilise KQL, SPL, SQL, log analysis, event correlation, and telemetry investigation to validate detection's and support investigations.Support continuous improvement of detection and response capabilities.

Stakeholder Management & Collaboration

Work closely with Security Operations, Detection Engineering, Threat Intelligence, Incident Response, and Global SOC teams.Act as a bridge between regional and global security functions.Deliver knowledge transfer sessions and operational walkthroughs.Translate complex technical concepts, detection logic, threat activity, and investigation outcomes into clear, business-friendly language.

Documentation & Governance

Maintain high-quality documentation of detection content and operational procedures.Ensure traceability between detection logic, threat mappings and analyst workflows.Support audit and compliance requirements through robust process documentation.

Essential Skills & Experience

Minimum 4 years' experience as a Tier 2 SOC Analyst (or recent Tier 3 experience).Strong background in security incident investigation, threat analysis, and threat hunting.Experience reviewing, tuning and validating detection rules and security alerts within SIEM platforms such as Microsoft Sentinel, Splunk, QRadar, ArcSight, Exabeam, or LogRhythm.Experience working with Microsoft Defender XDR, Microsoft Defender for Endpoint, CrowdStrike Falcon, Cortex XDR, SentinelOne, Carbon Black, or similar EDR/XDR technologies.Proven experience creating SOPs, playbooks, SOAR workflows, or response procedures for SOC teams.Strong understanding of attacker tactics, techniques and procedures (TTPs).Experience mapping detections to recognised threat frameworks such as MITRE ATT&CK.Experience using KQL, SPL, SQL, or similar query languages for investigation, threat hunting, and alert validation.Ability to define escalation criteria and investigation workflows.Experience working across multiple security teams and stakeholder groups.Strong communication skills with the ability to mentor and guide junior analysts.

Desirable Experience

Security transformation, SOC modernisation, or globalisation projects.Detection engineering experience.SOAR workflow, automation, or response procedure development.Quality assurance of SOC processes and detection content.Experience within financial services or highly regulated environments.Experience delivering analyst training and knowledge transfer sessions.Experience working within Azure, AWS, or GCP cloud environments.Experience with threat intelligence integration, detection use case development, and security monitoring strategy.

Qualifications

Degree in Cyber Security, Information Security, Computer Science, or equivalent practical experience.Relevant security operations, incident response, or monitoring certifications.Industry certifications such as Security+, CySA+, GCIH, GCIA, CISSP, SC-200, SC-300, AZ-500, or equivalent are advantageous.

Ideal Candidate

The ideal candidate is a genuinely senior SOC professional, not simply a Detection Engineer or Tier 1 Analyst. You will have a broad Security Operations background covering incident investigation, threat analysis, detection engineering, playbook development, stakeholder management, and mentoring.

You will be comfortable operating between regional and global teams, driving consistency across security operations and helping shape how detection and response capabilities are delivered at scale.

This is an excellent opportunity for a senior SOC professional looking to influence a large-scale Security Operations transformation while remaining technically hands-on.

GCS is acting as an Employment Agency in relation to this vacancy.

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Associate Machine Learning Engineer (Remote)

Remote (USA)

About the Role

We are seeking a talented and motivated Machine Learning Engineer I to join our growing team. This is an exciting opportunity for an early-career professional who is passionate about building machine learning solutions that create meaningful user experiences at scale.

The ideal candidate enjoys solving complex problems, writing production-quality code, and collaborating with cross-functional teams to develop and deploy intelligent systems. You will work closely with data scientists, software engineers, and product teams to build and optimize machine learning models that drive business impact.

Key ResponsibilitiesDevelop, train, and deploy machine learning models for personalization, recommendations, and customer-focused applications.Build scalable data pipelines for feature engineering, model training, evaluation, and inference.Collaborate with data scientists and software engineers to transition research and prototypes into production systems.Improve recommendation and ranking models using large-scale behavioral and engagement data.Monitor and evaluate model performance through experimentation, A/B testing, and data-driven analysis.Write clean, maintainable, and efficient Python code following software engineering best practices.Support initiatives that enhance customer engagement and business outcomes through machine learning solutions.Required QualificationsBachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, Statistics, Mathematics, Engineering, or a related quantitative field.1-3 years of relevant experience, including internships, research, academic projects, or professional experience.Strong programming skills in Python.Solid understanding of machine learning fundamentals, including:Supervised learningClassification and regressionFeature engineeringModel evaluation and validationExperience with machine learning frameworks such as Scikit-learn, TensorFlow, or PyTorch.Experience working with SQL and large datasets.Familiarity with Git and software development best practices.Strong analytical and problem-solving skills.Why Join Us?Work on machine learning products that impact large-scale user experiences.Collaborate with highly skilled engineers, data scientists, and researchers.Gain hands-on experience deploying production-grade machine learning solutions.Grow your expertise in modern ML technologies and scalable systems.Flexible remote work environment with opportunities for learning and career development.

GCS is acting as an Employment Business in relation to this vacancy.

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What you'll be doing

Reviewing automated RF-plant analysis and validating it against what is actually happening on the network - confirming the platform isn't misreading or over-stating the data.Sanity-checking the interpretation of RF performance, signal behavior, and physical-layer impairments across the plant.Assessing the platform's predictive trending - whether its "this is starting to degrade" calls hold up against real-world DOCSIS RF expertise.Delivering a clear, expert read on what's solid, what's inaccurate, and what additional signals should be considered.

What we're looking for

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We're looking for DOCSIS Engineer and you'll review the platform's RF-plant analysis and confirm it reflects what is genuinely happening on a live DOCSIS network. You'll be the human authority that tells the client "yes, this is right" or "here's where it's off, and here's what it's missing."

What you'll be doing

Reviewing automated RF-plant analysis and validating it against what is actually happening on the network - confirming the platform isn't misreading or over-stating the data.Sanity-checking the interpretation of RF performance, signal behavior, and physical-layer impairments across the plant.Assessing the platform's predictive trending - whether its "this is starting to degrade" calls hold up against real-world DOCSIS RF expertise.Delivering a clear, expert read on what's solid, what's inaccurate, and what additional signals should be considered.

What we're looking for

Deep, hands-on DOCSIS RF / HFC physical-layer expertise- gained at a cable operator (MSO) or equipment vendor.Strong ability to read RF plant performance- spectrum behavior, signal levels, noise and impairments - not just protocol or IP-layer data.Practical live-plant diagnostic experience- sweep/balance, signal forensics, and proactive network maintenance (PNM)-style analysis.Solid DOCSIS 3.1 and 3.0 knowledge.Comfort reviewing and critiquing analytic output- forming and clearly communicating an expert verdict.

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