Senior Data Scientist

Who are we?

[Employer hidden] (also known as Qualis Flow) was founded in 2018 with a bold mission: to provide the data that empowers the world to build responsibly. We’re building a cutting-edge platform that enables project teams with real-time insights on materials, waste, cost, carbon, and quality, right at the source. [Employer hidden] is helping cut waste and reduce carbon emissions by providing construction and development teams with the data-driven insights they need to deliver productive, profitable and sustainable projects. Our vision is one of a future where the way we build heals the planet and elevates humanity.

We combine AI, machine learning, and powerful integrations to make sense of chaotic, unstructured data streams. Our technology automatically extracts and structures data from the messiest receipts and documents, audits it against project requirements, flags risks instantly, and seamlessly integrates insights into reporting workflows. Our mobile app makes it effortless for workers on the ground to capture data in seconds — turning construction sites into real-time, data-rich ecosystems.

We’re backed by leading climate-tech and construction-tech investors including Systemiq Capital, Greensoil PropTech Ventures, and Suffolk Technologies, and have raised £11.2M in Series A funding to accelerate our international growth.

Your role and responsibilities

• Demonstrated experience in researching, prototyping and deploying AI/ML solutions in production.
• Collaborate with stakeholders to identify and understand business needs, translating them into data-driven solutions.
• Perform exploratory data analysis (EDA) to uncover trends and patterns.
• Develop and apply advanced statistical and machine learning models to solve business problems, including forecasting, segmentation, optimization, and predictive modelling.
• Conduct rigorous data analysis, interpret results, and communicate findings to technical and non-technical audiences.
• Stay abreast of emerging technologies and industry best practices in data science.
• Contribute to the development of a data-driven culture.
• Champion best practice in coding, version control, documentation and automation.

Your skills

• Strong experience in a data-focused environment with an emphasis on building scalable, high-performance predictive models
• Advanced proficiency in Python, SQL and modern machine learning frameworks
• 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
• Demonstrated ability to identify opportunities and drive projects from concept to completion
• Proven track record in delivering high-quality code through test-driven development, pair programming, and collaborative development practices
• Excellent communication and interpersonal skills
• Strong mentorship capabilities
• Thrives in a fast-paced, ambiguous start-up environment

Our Tech Stack

C#, React, TypeScript/JavaScript, Python, .NET Core, Azure DevOps, RESTful APIs, Distributed Systems, Asynchronous Services, Distributed Storage, Azure Tables, SQL Server and Cosmos, Redis, xUnit and Terraform

Our offer

• Salary competitive depending on experience
• Remote-first team (we enjoy meeting up from time to time in our London HQ)
• Company laptop and tools
• 25 days annual leave + 3 days company closure at Christmas + bank holidays
• Paid sick leave
• Private medical insurance
• Critical illness and life insurance
• Pension contribution up to 7%
• Enhanced family policy
• Paid volunteering days
• Work abroad for up to 90 days
• We’ll offset your annual carbon footprint via Ecologi
• Learning & development and career progression opportunities
• Company social events (online and in person!)

Our promise

Creating an environment where everyone feels valued, respected and heard. We are committed to providing equal employment opportunities regardless of race, colour, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or veteran status.

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