Senior Machine Learning Scientist

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.

What's the opportunity?

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 focussed 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.

What will I be doing?

Identify areas where ML can create value for our customers

Identify the right ML framing of product problems

Working 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

Being pragmatic, but innovating right 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

What skills might I need?

Broad applied machine learning knowledge

3-5 years applied ML experience

Practical stats knowledge (experiment design, dealing with confounding etc)

Intermediate programming skills

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

Bonus skills & attributes

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

Visualization, data skills, SQL, matplotlib, etc.

Benefits

We are a well treated bunch, with awesome benefits! If there’s something important to you that’s not on this list, talk to us!

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

Regular compensation reviews - we reward great work!

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, to let you spend valuable time with your loved ones

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

Policies

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.

We have a radically open and accepting culture at Fin. We avoid spending time on divisive subjects to foster a safe and cohesive work environment for everyone. As an organization, our policy is to not advocate on behalf of the company or our employees on any social or political topics out of our internal or external communications. We respect personal opinion and expression on these topics on personal social platforms on personal time, and do not challenge or confront anyone for their views on non-work related topics. Our goal is to focus on doing incredible work to achieve our goals and unite the company through our core values.