Director of Business Development

a leading IT services company
London
2 months ago
Applications closed

Related Jobs

View all jobs

Director of Data Science & Analytics

Lead Machine Learning Engineer, Associate Director, London

Business Development Director

Director of Artificial Intelligence - Manufacturing & Industrial

Director of Product - City of London

Director of Healthcare Analytics

A leading IT services company in the London Area, United Kingdom.

Check you match the skill requirements for this role, as well as associated experience, then apply with your CV below.We specialize in driving digital transformation for the Banking, Financial Services, and Insurance (BFSI) sectors, using cutting-edge technologies like AI, Machine Learning, Blockchain, and Cloud Computing to enhance operations, improve customer experience, and enable new revenue channels.Our services include omni-channel customer engagement, regulatory compliance, and innovative financial solutions—all aimed at modernizing and enhancing how financial institutions engage with their customers.Key Responsibilities:New Business Development: Identify and acquire new clients within the BFS sector, focusing on large and strategic accounts.Sales Strategy: Develop and execute sales strategies to achieve and exceed revenue targets.Client Engagement: Build strong relationships with key decision-makers at potential client organizations.Solution Selling: Collaborate with internal teams to tailor solutions that meet client needs.Pipeline Management: Maintain and track a robust sales pipeline, ensuring timely follow-ups.Negotiations & Closing: Lead negotiations and close deals, aligning them with company goals.Global Delivery Model: Sell projects using onsite-offshore and global delivery models to optimize client satisfaction.Collaboration: Work closely with delivery, marketing, and other internal teams to ensure smooth project execution.Qualifications:8-15 years of experience in business development, sales in Banking and Financial Services for an IT Services company, Digital company or Consulting firm.Demonstrated track record of increasing revenue through generation of leads.Strong communication and negotiation skills.Strong connects in Banking and FS industry at CXO level in the UK market.Diversity & Inclusion:

We encourage diverse candidates to apply. We believe that a diverse workforce drives creativity and innovation, and we are committed to creating an inclusive space where every individual can thrive.If you're ready to drive innovation, tackle industry challenges, and grow your career within a forward-thinking organization, apply now and take the next step in your professional journey!Seniority level DirectorEmployment type Full-timeJob function Sales and Business DevelopmentIndustries IT Services and IT Consulting, Technology, Information and Media, and Business Consulting and Services

#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.

Jobs

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!

Jobs Careers

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.

Jobs

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.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.