As Technical Writer you will lead QuantumBlack's communication of the expertise of our data scientist, data engineers, designers and other disciplines with the rest of McKinsey as well as external users. This role is critical in helping internal and external people learn and understand how we operate, our methodology and best practices, and our tools.

All our content is continually growing with contributions from different disciplines and new learnings from projects we work on with our clients. Over the past year we have created over 50,000 words of new best practices and activities. These contributions are written by internal teams themselves in an organic way from their experience.

You will be instrumental to help the different voices and disciplines come together into one representation of QuantumBlack's way of working, establishing contribution guidelines and being the advocate and gatekeeper of quality and accessibility of the content.

Main Responsibilities

As our business and content keep increasing we face the challenges of enabling more teams to contribute to our materials whilst ensuring quality doesn't deteriorate over time.

As the leading Tech Writer you will:

  • Lead interviews to understand what teams think, operate and can share.
  • Document findings into a format that can be shared and easily understood across QuantumBlack and McKinsey taking into consideration different audiences (from novices to matter experts).
  • Create content about best practices such as ‘How do I ingest data sources?’ or ‘How do I set up the right infrastructure?’ or ‘How do I engineer features?’. This will be process heavy, step-by-step content. The content won’t be teaching someone how to be a data engineer, but it will be explaining how a data engineer is expected to work within QuantumBlack.
  • Work with the product managers to publish product and feature updates about the several technologies we have built to support the best practices.
  • Ghost-write long-form opinion pieces on process or potentially two-way debates between two members of the staff. 
  • Lead and collaborate with other tech writers across multiple streams of work

Key skills

  • Collaborative and research skills: You will work with multi-disciplinary teams across QuantumBlack. This will include Data Scientist, Data Engineers, Machine Learning Engineers, Product Managers and Designers. A crucial part of this role is gaining insight into how people operate and their domain knowledge and translate that for others to learn and apply.
  • Written and verbal communication skills: Both speaking and writing abilities are key in this role. You will be the standard for how people communicate and operate across QuantumBlack and McKinsey on advanced analytics projects.


  • Proven skills in understanding and simplifying complex concepts.
  • Ability to interviewing staff and ghost-writing on their behalf. 
  • Present content in meetings and embrace and incorporate feedback.
  • Comfortable in adopting existing tones of voice and ability to fit new content into existing narratives.
  • Ability to work in a fast paced environment and comfortable with chaos and a 80/20 approach to getting things done.

What you'll learn

We are passionate about life-long learning and professional development. You will have different areas you are excited to develop and we will support those. We would expect that anyone in this role will develop skills in:

  • Stakeholder communication within large organisations
  • Content production, guidelines definition and optimisation
  • Organisational skills, knowledge and experience of working with technical products
  • Knowledge of advanced analytics and machine learning practices 


  • London

Visit our Careers site to watch our video and read about our interview processes and benefits

As an equal opportunity employer, QuantumBlack encourages applications from all backgrounds regardless of gender, race, disability, pregnancy, marital status, age, sexual orientation, gender reassignment, religion or belief. We maintain a sense of community rooted in respect and consideration for all employees where any evaluation is based simply upon individual work and team performance.

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