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autone
London Office
Full time
Hybrid
Tech
Autone is transforming retail with AI-driven inventory intelligence.
We’re on a mission to reimagine the future of retail. Combining cutting-edge AI with deep industry expertise to help global brands make smarter, waste-free decisions that drive growth and efficiency.
Trusted by 50+ leading brands and backed by Y Combinator and General Catalyst, we’re scaling fast to build the technology that makes supply chains cleaner, leaner, and more agile.
A passionate Data Scientist with expertise in statistical and machine learning models to help us reimagine demand forecasting and inventory optimisation. If you’re excited about building and deploying models that solve real-world problems, we’d love to hear from you.
Partner with product managers and engineers to translate requirements into technical solutions
Implement, monitor, and deploy advanced statistical and machine learning models for demand planning and inventory optimisation
Contribute to our tech stack, tooling, and processes to strengthen ML/AI capabilities.
Conduct code reviews and champion best practices for model explainability, monitoring, and performance
Languages: Python, SQL (Postgres)
ML/AI libraries: PyTorch, scikit-learn, Polars
Infrastructure: Docker, AWS Sagemaker, EKS, Lambda, Athena
Orchestration & data tools: Dagster, ClickHouse, MLFlow
We’re technologically adaptable: experience with similar tools is valuable, and we welcome fresh ideas that improve our workflows.
You’ll succeed here if you have:
A strong STEM background (degree or equivalent hands-on experience)
Experience as a Data Scientist or similar role (startup/scaleup experience is a plus—we’re open to exceptional candidates outside this range)
Proven expertise in time series analysis, predictive algorithms, forecasting models, and optimisation techniques (e.g., loss functions, constrained optimisation, Bayesian methods)
Proficiency in Python and libraries such as scikit-learn, Pandas/Polars, and PyTorch
Strong SQL skills
Experience deploying, monitoring, and analysing the performance of ML models
Nice-to-haves:
Retail or e-commerce domain knowledge
Familiarity with AWS or GCP tools ( EKS/GKE, Lambda/CF, Athena/BigQuery)
Experience with MLFlow or similar model management tools
Familiarity with Dagster or other orchestration tools (e.g., Airflow)
High impact: your models will shape the way major global brands plan, buy, and move products
Creative freedom: significant ownership over model development and deployment, with room to innovate
Career growth: A meritocratic, high-growth environment where your trajectory is yours to steer
Team culture: Pub quizzes, canoeing trips, team breakfasts and lunches, an annual all-company retreat, and more - we believe great ideas come from collaboration, curiosity, and a bit of fun
Compensation: £65–90k base salary plus meaningful equity, depending on experience
Location & flexibility: London-based with a hybrid-friendly setup (we value in-person collaboration but support flexible work)
Inclusivity: we’re committed to building a diverse, inclusive team and encourage applications from all backgrounds.
We value transparency and aim to complete the process within 2–3 weeks:
CV screen (30 min) + live-coding Python exercise (45 min) – introductory chat and collaborative coding
Machine learning brainstorm (1 hr) + Cultural fit (30 mins) – work with potential colleagues on challenges similar to those we face daily
Meet a C-level leader (30 min) – Learn more about our vision and goals directly from a founder or another executive.
Compensation Range: £65K - £90K
