Senior Data Scientist - Operational Research & Optimisation
Dayjob is the AI business that is bringing advanced logistics and optimisation to the trade economy - a £25bn market where planning is still done manually. From plumbers to skip hire, we’re replacing outdated planning with real-time, AI-powered dispatching that models how work is distributed across fleets. Our platform uses ML and heuristic algorithms inspired by the best in logistics, ride-sharing, and operations research to drive efficiency.
Since launch, we’ve onboarded paying customers and are working with leading waste and recycling firms across the UK. Our goal is to eliminate manual planning tasks and turn back-office teams’ workloads into proactive, real-time activities. We closed our pre-seed in 2024 and are now scaling the team toward £1M ARR.
If you dream at night of building the same tech that powers the likes of Uber or Deliveroo but applying it to the industries that keep the world moving, this is the role for you.
Founding Team
Fred & George met at the University of Oxford.
George (CEO) was Head of Sales at Otta and launched the Grocery division at Deliveroo, scaling it to £100M GMV.
Fred (CTO) is an expert in building products that optimise complex supply chains using AI and advanced analytics.
Joe (Lead Engineer) has built software at Sky, DAZN, and Bulb and was previously Tech Lead at Otta, scaling from 100k to 1.5m users.
The Role: Senior Data Scientist – Operations Research
This is a rare opportunity to join as our founding data scientist to build and own the models that power the Dayjob platform. You’ll work directly with the founders and customers to design, test, and scale optimisation algorithms in real-world environments.
Candidate Description:
You’re deeply curious and pragmatic, and you care about solving real-world operational problems. You’ve built and deployed optimisation algorithms that balance multiple constraints in fast-changing systems.
You have:
* Have a degree in mathematics, physics, computer science, data science or similar
* 4+ years of experience working on optimisation, routing, scheduling, or applied OR problems
* Extensive experience in developing Optimisation or machine learning solutions, ideally in a fast-paced company focusing on transportation/logistics
* Strong Python and SQL skills, ideally with experience using solvers (e.g. OR-Tools, Gurobi, CPLEX)
* The ability to balance theoretical rigour with pragmatic constraints
Bonus if you’ve worked on:
* Vehicle routing problems (VRP), especially with time windows, capacities, or traffic
* Constraint programming or metaheuristics
* Real-time systems or streaming data
* Start-up experience preferred
What the Job Involves:
* Design and implement the algorithms that will power Dayjob
* Work directly with customers to understand real-world constraints and edge cases
* Prototype quickly, then productionise in collaboration with the engineering team
* Shape our long-term data strategy and technical roadmap
* Build internal tools to evaluate performance, trade-offs, and impact
What We Offer:
* Meaningful equity
* 25 days holiday + your birthday off
* Flexible working (remote-friendly, office in Camden)
* A key role in defining our product and algorithms from the ground up
Application Process:
* Intro call with the team (30 mins)
* Take home problem-solving task (2 hours)
* Technical interview (60 mins)
* Final chat with founders (45 mins)
Want to build the brains of the next-gen dispatch engine? We’d love to hear from you.
Send me alerts about jobs like this.
Please enter your email address to continue setting up an email alert for similar jobs to this one. By entering your email address and clicking apply you will sign up to Jobs4 and agree to our terms and conditions .
Job Overview
ID:
1524477
Date Posted:
Posted 20 hours ago
Expiration Date:
28/06/2025
Location:
London
Competitive
Send me alerts about jobs like this.
Please enter your email address to continue setting up an email alert for similar jobs to this one. By entering your email address and clicking apply you will sign up to Jobs4 and agree to our terms and conditions .
Share
Complete the form below to send this job to a friend.
Job Location
Complete the form below to report this job.
#J-18808-Ljbffr