Below covers everything you need to know about what this opportunity entails, as well as what is expected from applicants.About us:

Autone is reimagining the future of retail with cutting-edge AI-driven intelligence, empowering brands to make smart, waste-free decisions that drive growth and efficiency. Trusted by over 50 global brands, we blend advanced AI and deep retail expertise to unlock seamless collaboration between supply chains and human insight. The result? Reduced inventory waste, boosted sales, and precise forecasting that saves money and enhances operations - all while empowering teams to focus on what they do best.

Founded in London in 2021 and backed by industry giants like Y Combinator & General Catalyst, Autone is moving fast to transform retail as we know it. Join us on this journey to a smarter, more agile future.

Joining Autone means working alongside some of the brightest minds to disrupt the retail industry for a better future. We prioritize in-office work for fostering collaboration, with most of our team in our Vauxhall office 3-4 days a week. We're flexible when it matters, but this role is primarily on-site and not suitable for someone seeking a fully remote position.

And now to you!

We’re looking for a passionate & optimistic

senior data scientist

to join our growing product team. As a data scientist, you’ll work closely with our CEO, CTO and stellar data team to develop and improve our statistical models with a focus on demand forecasting and inventory optimisation. You will have ownership over developing and deploying cutting-edge statistical / ML models, as well as shaping our codebase.

Your responsibilities:

Collaborate with the product team to understand requirements and provide technical solution

Implement, monitor and deploy advanced statistical / ML models to solve our customers demand planning and inventory optimisation needs.

Shape our future tech-stack and tooling to enhance ML/AI capabilities

Review code from colleagues

Improve data science processes, visibility and explainability perhaps by introducing new data tools or technologies

What we are looking for:

A minimum of 2:1 degree in a STEM subject (preferably Computer Science) or comparable experience

5-8 years of experience as a data scientist / machine learning engineer, preferably with some experience in an early stage startup! Domain knowledge in retail/commerce is also a plus

Experience with time series problems, predictive algorithms, and machine learning approaches to forecasting

and/or

experience with optimization algorithms, including loss functions, constrained-optimization, Bayesian models, etc.

Experience with tooling for deploying, monitoring, analysing performance and iterating on models

You relish the thought of taking a large role in an early stage startup and steering its Data Science / ML direction.

Advanced knowledge of Python with strong experience with common libraries such as scikit-learn, Tensorflow, Pandas, PyTorch, and/or statistical models.

Strong SQL knowledge

Experience with AWS is a plus

Experience with a tool like MLFlow is a plus

Someone who enjoys working in-office

The tech stack you’ll be working with

Python

SQL (Postgres)

Tensorflow / PyTorch / sci-kit learn / pandas

Docker

Dagster

AWS Sagemaker, EKS, EMR, Lambda, Athena

ClickHouse

Spark

We pride ourselves on being technologically agnostic, so while this is the current state of our tech-stack, we’re always open to new ideas and technologies that can improve the way we do things. Proficiency in Dagster and listed AWS technologies not necessarily required but experience in similar analogous data tools would be e.g. Airflow, ECS etc.

Why you’re going to love joining the team

Ability to have a huge impact within an early stage company, working directly with the founders

Being hands on with an agile and modern-tech stack with freedom to employ new technologies to achieve goals

Meritocratic driven career growth

Fortnightly team events - games nights, sporting events or even just a trip to our local pub

A competitive compensation package (including stock options)

The interview process

CV Screen (45mins) - A chat around your previous work experience as well as an introduction to autone and a chance to find out what we do here

Data Science Brainstorm (1hr) - work with some potential future colleagues to ideate around a series of challenging data science problems relevant to autone

Meet a Co-Founder (30mins) - a chance for you to learn more about the company and our grand ambitions

#J-18808-Ljbffr