Bid Manager

ABB Schweiz AG
2 months ago
Applications closed

Related Jobs

View all jobs

Project Engineer

Senior Data Scientist

Bid ManagerAt ABB, we are dedicated to addressing global challenges. Our core values: care, courage, curiosity, and collaboration - combined with a focus on diversity, inclusion, and equal opportunities - are key drivers in our aim to empower everyone to create sustainable solutions. Write the next chapter of your ABB story.
This position reports to

Brownfield Bid Manager Team Lead

Your role and responsibilities

In this role, you will have the opportunity to manage bid content and produce high quality tenders, collaborating with the front-line Sales function and Technical Advisory team for ABB’s Energy Industries business in the UK. The work model for the role is remote.

You will be mainly accountable for:

  1. Supporting the field Sales team and generating proposals for the Lifecycle services and solutions parts of the business, that support the sales strategy for that opportunity.
  2. Manage the end-to-end bid process, including reviewing requests for proposals (RFPs), preparing bid documents, and submitting proposals.
  3. Ensure compliance with legal, financial, and technical standards in all bid submissions.
  4. Compiling or generating bid content on an individual bid/proposal basis e.g. executive summaries, customer business needs/requirements.
  5. Collaborating with the Tender Manager, Commercial Manager and engaging with financial and legal teams for support as required.
  6. Track and manage bid timelines, milestones, and deliverables.
  7. Collating numerical bid content/estimates and generating Cost Models.
  8. Presentation of Cost Models to Sales and Operations.
  9. Supporting Review process to gain Sales and Operational approval in order to submit bids by the due date.
  10. Requesting Approval to Issue through the Sales and Tenders Approval Tool and issuing the bid to the client (or via sales responsible).
  11. Organising hard copies of tenders when required, including binding, packaging and delivery.
  12. Continuing to improve the standard and quality of bids.

Qualifications for the role

  • Capable of coordinating the bid activity and inputs from a virtual cross-business team of individuals which changes on each tender requirement.
  • Capable of planning scopes of work.
  • Flexibility to work under pressure and meet tight deadlines.
  • Proficient in the Microsoft Office Suite, with a strong focus on Microsoft Word and Excel.
  • A reasonable understanding of Quality and IT systems or capability to assimilate these systems, including IMS, Salesforce and SharePoint.
  • Awareness/understanding of the Energy Industries services would be an advantage.
  • Experience of handling financial data / understanding of cost models - desirable.
  • Experience of commercial tendering - desirable.
  • An ability to handle and process large amounts of spreadsheet data - desirable.
  • Proficiency in low-level programming or scripting to automate workload, including the processing of document and numbers from customers or suppliers - desirable.

More about us

For the 5th consecutive year, ABB is recognised as a Top Employer in the UK. Being certified as a Top Employer showcases an organisation’s dedication to a better world of work and exhibits this through excellent HR policies and people practices. The Energy Industries Division serves a wide range of industrial sectors, including hydrocarbons, chemicals, pharmaceuticals, power generation and water. With its integrated solutions that automate, digitalize and electrify operations, the Division is committed to supporting traditional industries in their efforts to decarbonize. The Division also supports the development, integration and scaling up of new and renewable energy models. The Division’s goal is to help customers adapt and succeed in the rapidly changing global energy transition. Harnessing data, machine learning and artificial intelligence (AI), the Division brings over 50 years of domain expertise delivering solutions designed to improve energy, process and production efficiency, as well as reduce risk, operational cost and capital cost, while minimizing waste for customers, from project start-up and throughout the entire plant lifecycle.

#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.