Cyber Defence Principal Consultant

RiverSafe Ltd.
London
1 month ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Machine Learning Consultant - Experienced

RF Design Engineer - LNAs, Design from LF to X Band

Digital Design Engineer - High Speed Digital Design

Data Engineer

Senior Recruiter

Make an impact with your next career moveEmployment

Full-time

Location

London (Canary Wharf) Office / hybrid

Function

Professional Services

The Company

RiverSafe is a premier Cyber Security consultancy based in the heart of Canary Wharf and we are meeting the huge demand we have seen head on! We have a proven track record of delivering services to a well-known client base including FTSE 100 companies and are partnered with market leading technology vendors including Splunk, Palo Alto, Exabeam and AWS.

The Role

A Cyber Defence Principal Consultant finds solutions to ensure enterprise deployments make the deepest impact possible across an organisation. Our principals solve organisation’s most challenging problems, including the ones they didn’t know existed. They are self-motivated, have an insatiable thirst to learn new technologies and thrive in a fast-paced environment. Successful RiverSafe security principals feel comfortable mastering new technologies and come from a variety of business, analytic and technology backgrounds with experience managing diverse teams and clients.

Key Responsibilities

  • Work within our Cyber Defence and Big Data practice and manage teams and client engagements.
  • Oversee the completion of security assessments or technical delivery elements of security transformation programmes.
  • Create high-quality reports that meet customer requirements.
  • Identify opportunities for RiverSafe to assist clients and escalate to the engagement manager.
  • Establish and build a network of contacts within our clients.
  • Assist with the planning and delivery phases of engagements with our Service Delivery Team.
  • Contribute to the creation of proposals and marketing material.
  • Ensure work is delivered on time and on budget.
  • Develop the existing team by sharing knowledge and leading by example.

Skills

  • Experience in managing security consultants.
  • Demonstrable consulting experience and strong relationship-building skills.
  • Experience with SIEM products like Splunk, Exabeam, ArcSight, Sentinel, or other IPS/IDS products.
  • Experience in security transformation programmes and risk management.
  • Knowledge of Cloud security and Big Data Analytics.
  • Experience in breach and incident management practices.
  • Familiarity with agile development environments.
  • Ability to create secure architecture designs and conduct architectural reviews.
  • Proficiency with Unix and Windows operating systems.
  • Strong networking fundamentals and communication skills.
  • Aptitude for understanding complex problems and customer needs.

What We Offer

  • Great culture in an exciting and fast-growing company.
  • Modern office with games and refreshments.
  • Regular company socials, events, and dinners.
  • A diverse and collaborative environment.
  • Opportunity to grow and lead as the business expands.
  • Paid holiday (22 days + Bank Holidays).
  • Personal learning & development fund.
  • Private healthcare including mental health support.
  • Pension Scheme.
  • Cycle to Work Scheme.

Apply For This Role

First name *

Last name *

Email *

Phone number *

Role Interested In *

Upload CV *

J-18808-Ljbffr

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Portfolio Projects That Get You Hired for Machine Learning Jobs (With Real GitHub Examples)

In today’s data-driven landscape, the field of machine learning (ML) is one of the most sought-after career paths. From startups to multinational enterprises, organisations are on the lookout for professionals who can develop and deploy ML models that drive impactful decisions. Whether you’re an aspiring data scientist, a seasoned researcher, or a machine learning engineer, one element can truly make your CV shine: a compelling portfolio. While your CV and cover letter detail your educational background and professional experiences, a portfolio reveals your practical know-how. The code you share, the projects you build, and your problem-solving process all help prospective employers ascertain if you’re the right fit for their team. But what kinds of portfolio projects stand out, and how can you showcase them effectively? This article provides the answers. We’ll look at: Why a machine learning portfolio is critical for impressing recruiters. How to select appropriate ML projects for your target roles. Inspirational GitHub examples that exemplify strong project structure and presentation. Tangible project ideas you can start immediately, from predictive modelling to computer vision. Best practices for showcasing your work on GitHub, personal websites, and beyond. Finally, we’ll share how you can leverage these projects to unlock opportunities—plus a handy link to upload your CV on Machine Learning Jobs when you’re ready to apply. Get ready to build a portfolio that underscores your skill set and positions you for the ML role you’ve been dreaming of!

Machine Learning Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Machine learning is fuelling innovation across every industry, from healthcare to retail to financial services. As organisations look to harness large datasets and predictive algorithms to gain competitive advantages, the demand for skilled ML professionals continues to soar. Whether you’re aiming for a machine learning engineer role or a research scientist position, strong interview performance can open doors to dynamic projects and fulfilling careers. However, machine learning interviews differ from standard software engineering ones. Beyond coding proficiency, you’ll be tested on algorithms, mathematics, data manipulation, and applied problem-solving skills. Employers also expect you to discuss how to deploy models in production and maintain them effectively—touching on MLOps or advanced system design for scaling model inferences. In this guide, we’ve compiled 30 real coding & system‑design questions you might face in a machine learning job interview. From linear regression to distributed training strategies, these questions aim to test your depth of knowledge and practical know‑how. And if you’re ready to find your next ML opportunity in the UK, head to www.machinelearningjobs.co.uk—a prime location for the latest machine learning vacancies. Let’s dive in and gear up for success in your forthcoming interviews.

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.