Senior Machine Learning Scientist (London)

Fin is the AI Customer Agent company on a mission to help businesses provide perfect customer experiences.

Our AI Agent Fin is the highest performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always on customer support across the customer journey - from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end to end across every channel, with minimal set up and integration. Fin can also be combined with our natively integrated Intercom help desk for one single system that is designed to meet the needs of modern day support teams.

Founded in 2011, Fin became one of the fastest growing companies and remains one of the largest private software companies in the world with nearly 30,000 global businesses using our products to transform their customer support. Driven by our core values, we push boundaries, build with speed and intensity, and relentlessly deliver incredible value to our customers.

Fin's Machine Learning team is responsible for defining new ML features, researching appropriate algorithms and technologies, and rapidly getting first prototypes in our customers' hands.

We are an extremely product focused team. We work in partnership with Product and Design functions of teams we support. Our team's dedicated ML product engineers enable us to move to production fast, often shipping to beta in weeks after a successful offline test.

We are very passionate about applying machine learning technology, and have productized everything from classic supervised models, to cutting edge unsupervised clustering algorithms, to novel applications of transformer neural networks. We test and measure the real customer impact of each model we deploy.

• Identify areas where ML can create value for our customers
• Identify the right ML framing of product problems
• Work with teammates and Product and Design stakeholders
• Conduct exploratory data analysis and research
• Deeply understand the problem area
• Research and identify the right algorithms and tools
• Be pragmatic, but innovate to the cutting edge when needed
• Perform offline evaluation to gather evidence an algorithm will work
• Work with engineers to bring prototypes to production
• Plan, measure & socialize learnings to inform iteration
• Partner deeply with the rest of team, and others, to build excellent ML products

• Broad applied machine learning knowledge
• 3 5 years applied ML experience
• Practical stats knowledge (experiment design, dealing with confounding, etc.)
• Strong communication skills, both within engineering teams and across disciplines
• Comfort with ambiguity
• Typically have advanced education in ML or related field (e.g. MSc)
• Scientific thinking skills
• Track record shipping ML products
• PhD or other experience in a research environment
• Deep experience in an applicable ML area. E.g. NLP, Deep learning, Bayesian methods, Reinforcement learning, clustering
• Strong stats or math background

• Competitive salary and equity in a fast growing start up
• We serve lunch every weekday, plus a variety of snack foods and a fully stocked kitchen
• Pension scheme & match up to 4%
• Peace of mind with life assurance, as well as comprehensive health and dental insurance for you and your dependents
• Flexible paid time off policy
• Paid maternity leave, as well as 6 weeks paternity leave for fathers
• If you're cycling, we've got you covered on the Cycle to Work Scheme. With secure bike storage too
• MacBooks are our standard, but we're happy to get you whatever equipment helps you get your job done
• Relocation support for those moving to our offices

Fin has a hybrid working policy. We believe that working in person helps us stay connected, collaborate easier and create a great culture while still providing flexibility to work from home. We expect employees to be in the office at least three days per week.

Fin values diversity and is committed to a policy of Equal Employment Opportunity. Fin will not discriminate against an applicant or employee on the basis of race, color, religion, creed, national origin, ancestry, sex, gender, age, physical or mental disability, veteran or military status, genetic information, sexual orientation, gender identity, gender expression, marital status, or any other legally recognized protected basis under federal, state, or local law.