Senior Data Scientist

About Autone

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.

What We’re Looking For

We’re on the hunt for a passionate Senior Data Scientist to join our team, bringing expertise in statistical and machine learning models to enhance demand forecasting and inventory optimization. If you're excited about building and deploying models that tackle real-world challenges, we’d love to hear from you.

Core Responsibilities:

• Collaborate with our product team to understand requirements and develop technical solutions.

• Implement, monitor, and deploy advanced statistical and machine learning models to address customer needs in demand planning and inventory optimization.

• Shape and enhance our tech stack, tooling, and processes to optimize ML/AI capabilities.

• Conduct code reviews and support ongoing improvements in data science processes, explainability, and visibility.

Tech Stack You’ll Be Working With

• Languages: Python, SQL (Postgres)

• ML/AI Libraries: TensorFlow, PyTorch, scikit-learn, Pandas

• Infrastructure: Docker, AWS Sagemaker, EKS, EMR, Lambda, Athena

• Orchestration & Data Tools: Dagster (or Airflow), ClickHouse, Spark
  
  We pride ourselves on being technologically adaptable. While the above is our current tech stack, we're open to new technologies that can improve our workflows. Experience with analogous tools is also valuable.

What You’ll Bring to Autone

Must-Haves:

• A 2:1 degree in a STEM field (preferably Computer Science) or equivalent experience.

• 5-8 years of experience as a Data Scientist or Machine Learning Engineer, ideally with some of that experience in a startup/scaleup.

• Strong experience with time series analysis, predictive algorithms, machine learning models for forecasting, and optimization algorithms (such as loss functions, constrained-optimization, and Bayesian models).

• Proficiency in Python and key libraries such as scikit-learn, TensorFlow, Pandas, and/or PyTorch.

• Strong SQL skills.

• Experience with tooling for model deployment, monitoring, and performance analysis.

Nice-to-Haves:

• Domain knowledge in retail or e-commerce.

• Familiarity with AWS (Sagemaker, EKS, EMR, Lambda, Athena).

• Experience with MLFlow or similar model management tools.

• Familiarity with Dagster or similar orchestration tools (e.g., Airflow).

What Autone offers you

• High Impact: As a Senior Data Scientist at Autone, you’ll have a central role in shaping our data science and ML strategy.

• Creative Freedom: Significant ownership over model development and deployment, with room to innovate.

• Career Growth: A meritocratic, high-growth environment where your career path is yours to steer.

• Team Culture: Fortnightly team events - from games to sports outings - and casual pub visits to foster team spirit.

Compensation

£90-£110K + equity, depending on experience

The Interview Process

We value transparency in our hiring process. Here’s what you can expect:

Stage 1: CV Screen (45 mins)

An introductory chat to explore your experience and provide an overview of Autone.

Stage 2: Data Science Brainstorm (1 hour)

Collaborate with potential colleagues on data science challenges relevant to our work at Autone.

Stage 3: Meet a Co-Founder (30 mins)

Learn more about our vision and goals directly from one of our founders.

Application Deadline

The deadline to apply is 23:59 GMT on Wednesday, 27th November 2024