Square One Resources
Data Scientist
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is a Data Scientist position for a 6–7 month contract in London (Croydon), offering approximately £55,000 annually. Key skills include Python, SQL, and experience in applied machine learning, particularly with geospatial and time-series data in logistics.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
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💰 - Day rate
250
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🗓️ - Date
March 3, 2026
🕒 - Duration
More than 6 months
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🏝️ - Location
Hybrid
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📄 - Contract
Fixed Term
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🔒 - Security
Unknown
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📍 - Location detailed
London Area, United Kingdom
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🧠 - Skills detailed
#Reinforcement Learning #Neural Networks #Data Science #Data Integration #ML (Machine Learning) #Python #Spatial Data #Databases #Datasets #SQL (Structured Query Language)
Role description
About the job
• Candidates need to be based in England and have full right to work
• Data Scientist – (Contract)
London (Croydon) (Hybrid – typically 3 days per week in office)
6–7 Month Contract (Strong likelihood of full-time conversion)
Approx. £55,000 annualised equivalent (depending on experience)
This is a hands-on applied machine learning role focused on building and improving decision systems that directly influence live fleet operations and contribute to long-term autonomous fleet orchestration capabilities.
You will work on logistics optimisation, real-time decision systems, simulation and operational experimentation, applying ML in complex, real-world environments.
What You’ll Work On
• Build predictive models using geospatial and time-series data (demand, driver behaviour, trip outcomes) and evaluate them using operational business metrics
• Partner with operations and senior team members to translate operational challenges into measurable ML problems and propose appropriate modelling approaches
• Engineer features, analyse large datasets using Python and SQL, and identify useful external data sources
• Design and support experiments contributing to fleet positioning and planning decisions
• Contribute to modelling and simulation work that supports long-term autonomous fleet orchestration and mixed-fleet (human driven + Autonomous Vehicle) operational planning
• Collaborate with operations and engineering to deploy and improve data-driven workflows
• Support related technical or analytical initiatives across the company (e.g. data integrations, tooling improvements, analytical inputs into product and operations)
We’re Looking For Someone Who
• Ideally has 3-5 years’ experience in Data Science / Applied ML / Analytics (years of experience provided as a guide)
• Can independently train, evaluate and iterate on models given a clearly defined problem
• Is comfortable with Python, strong SQL, and relational databases
• Can work with imperfect real-world data and optimise for practical impact rather than just model accuracy
• Has exposure to advanced modelling approaches (e.g. neural networks, optimisation, or reinforcement learning)
Nice to Have
• Experience with time-series or geospatial datasets, experimentation or optimisation problems
• Experience in logistics, marketplaces, mobility systems, ride-hailing or autonomous vehicle ecosystems
About the job
• Candidates need to be based in England and have full right to work
• Data Scientist – (Contract)
London (Croydon) (Hybrid – typically 3 days per week in office)
6–7 Month Contract (Strong likelihood of full-time conversion)
Approx. £55,000 annualised equivalent (depending on experience)
This is a hands-on applied machine learning role focused on building and improving decision systems that directly influence live fleet operations and contribute to long-term autonomous fleet orchestration capabilities.
You will work on logistics optimisation, real-time decision systems, simulation and operational experimentation, applying ML in complex, real-world environments.
What You’ll Work On
• Build predictive models using geospatial and time-series data (demand, driver behaviour, trip outcomes) and evaluate them using operational business metrics
• Partner with operations and senior team members to translate operational challenges into measurable ML problems and propose appropriate modelling approaches
• Engineer features, analyse large datasets using Python and SQL, and identify useful external data sources
• Design and support experiments contributing to fleet positioning and planning decisions
• Contribute to modelling and simulation work that supports long-term autonomous fleet orchestration and mixed-fleet (human driven + Autonomous Vehicle) operational planning
• Collaborate with operations and engineering to deploy and improve data-driven workflows
• Support related technical or analytical initiatives across the company (e.g. data integrations, tooling improvements, analytical inputs into product and operations)
We’re Looking For Someone Who
• Ideally has 3-5 years’ experience in Data Science / Applied ML / Analytics (years of experience provided as a guide)
• Can independently train, evaluate and iterate on models given a clearly defined problem
• Is comfortable with Python, strong SQL, and relational databases
• Can work with imperfect real-world data and optimise for practical impact rather than just model accuracy
• Has exposure to advanced modelling approaches (e.g. neural networks, optimisation, or reinforcement learning)
Nice to Have
• Experience with time-series or geospatial datasets, experimentation or optimisation problems
• Experience in logistics, marketplaces, mobility systems, ride-hailing or autonomous vehicle ecosystems
