At Qflow we’re on a mission to build a more sustainable future; providing construction and development teams with the data driven insights they need to deliver productive, profitable, and sustainable projects. Our team combines construction experience with software engineering and cutting-edge data science to deliver real-time alerts to risks and opportunities during construction.

You’re a talented Data Scientist looking for an opportunity to make a difference to one of the world’s most polluting industries. You enjoy working with the latest tech, and like finding ways to use it to solve real problems. We value radical transparency, unstoppable tenacity, collaboration, curiosity, and enduring ethics.

Your team and your role

We’re looking for someone to who will be responsible for leveraging data to drive business decisions. You’ll be involved in the entire data science pipeline from exploration and modelling to experimentation and deployment. We need a Data Scientist who can not only develop models but also bring them into production in collaboration with our Engineering team.

You’ll be working in our Data Science team, part of the wider Engineering function, working closely with Product and other technical teams and reporting to the team lead.

  • Identify valuable data sources and automate collection processes
  • Undertake pre-processing of structured and unstructured data
  • Analyse large amounts of information to discover trends and patterns
  • Design, develop, test, and deploy predictive models and machine learning algorithms
  • Present information using data visualisation techniques
  • Propose solutions and strategies to business challenges
  • Collaborate with engineering and product development teams
  • Write maintainable code, ensure it follows best practices, and document everything
  • Validate models and algorithmic performance through A/B testing and other techniques
  • Translate complex product requirements into data-driven solutions
  • Be a part of architectural decision-making, providing data-focused inputs
  • Provide technical mentorship in statistical modelling and machine learning to more junior members of the team
  • Keep an eye on the overall objective and business case, avoid getting caught up in the details and losing sight of the bigger picture

Your skills

  • Strong experience in a data-focused environment, with an emphasis on building scalable, high-performance predictive models
  • Expertise in Python, especially with libraries such as Pandas, and scikit-learn
  • Knowledge of machine learning frameworks like TensorFlow or PyTorch
  • Experience with data visualisation tools (e.g., Matplotlib, Tableau)
  • Experience in taking machine learning models from development into production
  • Familiar with fine tuning Large Language Models (LLMs) and prompt engineering
  • Familiarity with SQL and noSQL databases
  • Familiarity with cloud architecture, instrumentation, CI/CD, and git
  • Understanding of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests, and proper usage, etc.)
  • Excellent communication and interpersonal skills, with the ability to convey complex ideas and data to diverse audiences
  • Comfortable guiding and mentoring others in data science best practices
  • Some software engineering experience (software engineers with Data/ML/AI leanings are encouraged to apply)

Qflow's Tech Stack

Python, C#, JS/Typescript, React, Azure DevOps, RESTful APIs, distributed systems, asynchronous and synchronous services, distributed storage, Azure Tables, SQL Server and Cosmos, xUnit, Terraform.

Our Offer

  • Salary Range: £60,000 – £75,000, dependent on level of experience
  • Remote-first team – You can base yourself anywhere in the UK as long as you can easily make it to Qflow’s HQ in London for collaborative team meetings and fun social events.
  • Accessible HQ in central London – Step-free HQ in London close to Borough Market including prayer and meditation spaces, as well as many restaurants, cafes, and bars in the neighbourhood to enjoy after work.
  • Career opportunities – As Qflow scales, we help you to get access to tailored career progression plans and senior roles to reach your full potential.
  • Paid time off – 25 days annual leave (pro-rated for part-time roles) + bank holidays and paid sick leave.
  • Pension program – We provide a pension scheme for all permanent employees.
  • Learning and development – Opportunities to learn and grow with a dedicated budget
  • Social events – Regular company events from quiz nights to fun sport activities.
  • Company laptop and tools – The tech you need to do your work hassle- & stress-free.
  • Purpose and opportunity – To join a high-growth, VC-backed company and to make a positive impact. Construction is one of the most damaging industries to our climate. But it doesn’t have to be. It’s our goal to help make the industry sustainable and work in harmony with our environment.
  • Paid Volunteering days – We support what you are passionate about
  • Family Friendly Policy – Outstanding enhanced family policy
  • Carbon offset – We’ll offset your annual carbon footprint on your behalf via Ecologi

Our Promise

We at Qflow work every day with the purpose to leave the world in a better place than we found it. We respect the environment, and we respect each other. Qualis Flow is proud to be an equal opportunity employer.

Qflow does not discriminate against any employee or applicant because of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, physical or mental disability, age, marital status, pregnancy, or any other basis protected by law.

We value and encourage diversity within our workforce and are committed to promoting equality, while we maintain a work environment free from discrimination. All applicants will receive consideration for employment fairly and consistently, we adhere to these principles in all aspects of employment, including recruitment, hiring, training, compensation, promotion, benefits, social and recreational programs, and discipline.

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