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Senior Data Scientist / ML Engineer

Polar Analytics

Polar Analytics

Software Engineering, Data Science
Bristol, UK · London, UK · Manchester, UK · United Kingdom · London, UK · Germany · Spain · Bordeaux, France · Scotland, UK · Remote
Posted on Tuesday, June 4, 2024

Polar Analytics is a Full-Stack Business Intelligence Solution for Consumer Brands. A powerful, yet simple solution for business users to get the insights they need to succeed and make the right decisions.

Our mission is to empower indie DTC brands worldwide to grow faster and more profitably!

What's Unique About Polar Analytics? 💎

  • Traction - We've grown to over 2,000 + active merchants as of June 2023, and we're on track to reach 5,000 this year.

  • Tech & Product - We leverage the latest advancements of the modern data stack and make it user-friendly to non-technical users.

  • Funding Strategy - We're backed by Point9, an exceptional B2B SaaS investor that's renowned for finding Unicorns at an early stage.

  • Team - We're a collective of experienced individuals from leading eCommerce SaaS platforms and are on a mission to become the next unicorn.

Data Science @Polar 🎯

  • We are looking for individuals who love to create products and have ownership from inception to shipping.

  • You will work hand in hand with our data engineering, backend and product teams to deliver ML-based products at scale: create the infrastructure, start with MVPs and then expand!

  • As the #2 Senior Data Scientist, your mission at Polar will be critical: after achieving product market fit on our core BI offering and raising $24M, we are currently looking into expanding our capabilities and becoming more and more prescriptive.

    • We have a strong data infrastructure in place with a senior team of data engineers/scientists that you will work closely with Victor, Pierre, Alexis, Amaury, Charbel

What’s the scope 🔎

  1. Deliver high impact ML-based features in production, to empower thousands of entrepreneurs to grow their brand, with a product they use daily. Example: predict sales by SKU to help with inventory planning.

  2. Build an ML stack from scratch, that will allow us to scale and deliver dozens of models in production.

  3. Have strong ownership: identify and prioritise the right opportunities in a technical roadmap for Data Science.

  4. Work hand in hand with product to define the next big things

The job is made for you if...

  • You have delivered Time Series models in production, used by significant % of overall users

  • You are able to write production level code, mainly in Python & SQL, and are very familiar with software engineering concepts.

  • You have worked with ML Ops frameworks and understands the tradeoffs of building a stack from scratch

  • You have worked autonomously on features, and are able to unblock yourself.

  • You are driven by impact, thrive in a past-faced environment and are not afraid to deal with ambiguity and wear multiple hats.

Our stack 📚

We like to try new things out but most of our data stack is built around Python & SQL. Here are the things we use - and love:

  • dbt

  • Airflow

  • Airbyte & Fivetran

  • Snowflake

  • Kubernetes

  • Docker

  • Micro-services architecture on AWS + Glue / Spark

Our Hiring Process 📝

We follow a structured hiring process to ensure fairness and transparency. Our process may vary depending on the role, but this is what you can expect after you apply:

1. Recruiter Screen (30 mins): A call with our Head of Talent to talk through your current/past experience, your motivations and Tell you more about Polar Analytics.

2. Technical Fit (45 mins): Here, you'll meet either the Hiring Manager or a team member of a similar level to discuss your ways of working and understand your skillset and ability for the role.

3. Technical Deep Dive (1 hour): This interview usually consists of a practical element (case study, Presentation, Technical Problem Solving etc) designed to give you a broader understanding of how we drive impact at Polar. This will be with the hiring manager and one other team member.

4. Culture Interview (45 mins): A conversation with one of our Culture Champions. We assess your team fit based on our values (see below).

We value your time and effort in the application process, and we aim to provide feedback as quickly as possible.

Our Values 🌟

  • No Ego 🤝 - We're all about teamwork and valuing everyone's input.

  • Transparency 🪞 - Honesty, feedback, and open communication are cornerstones of our growth.

  • Growth Mindset 🚀 - We're always learning, improving, and striving for excellence.

  • Care for others 💜 - We're empathetic, customer-centric, and proactive in helping others.

  • Act Like the Owner 🔑 - We take responsibility and ownership to drive the success of our business.

  • Driven by Impact 🎯 - We focus on delivering value to our customers and stakeholders.

Company Perks & Benefits:

  • 🌎 Choice-first organisation with a culture built around impact rather than hours

  • 🏖 5 weeks of vacation

  • 💰 Competitive salary & equity (our compensation philosophy targets 60th - 80th percentile in the top 3 European tech markets)

  • 💻 Latest MacBook Pro or equivalent

  • 🏡 Remote Office Upgrade budget to spend in your first year to ensure you have the best environment possible to work in

  • 🩺 Complimentary private health insurance (we use Alan)

  • 😍 Every 6 months we organize a company-wide offsite to discuss where we're going and strengthen the social bonds