Machine Learning Operations Analyst
Data Science - London, England, United KingdomApply now
At Chattermill we use cutting-edge AI technology to give leading companies the key to improving their customer experience. We work with many of the most exciting companies in the world (Uber, HelloFresh, Transferwise, and Skyscanner to name a handful!) and are passionate about helping them put their customers at the heart of their decision making.
In our 6 years we’ve grown from two co-founders to a team of 50 (and counting) bright and diverse individuals. Chattermill was recently voted 16th in the Fastest growing tech companies in the UK by Deloitte and 77th in the fastest growing companies in Europe in the FT1000. We have ambitious plans to keep growing and are now looking for a Machine Learning Operations Analyst to join us in London and help us to glean insights from the terabytes of customer feedback data that our clients collect. This exciting role in the Machine Learning Operations team is highly collaborative and will work closely with a wide range of other teams and stakeholders including Data Science, Sales and Customer Success.
One of our core company values is that We are Obsessed with Experience and we are hoping that the right person shares this belief and wants to help empower our clients to deliver excellent customer experiences. They will do this through identifying important themes in clients’ customer feedback and maintaining the quality of data in the Chattermill platform.
As a Machine Learning Operations Analyst, you will:
- Help to scale our data processing pipeline while ensuring the excellent quality of our ML models
- Analyse and design data taxonomies that will work as the foundation for our algorithms to accurately provide clients’ insights
- Collaborate with the Data Science, ML Engineering and Product teams on the development of new data solutions, features and tools we create for both internal and client use
- Help to manage our remote data analyst teams
- Set and manage clients’ deadlines, and occasionally participate in client-facing calls
- Develop knowledge and advise on best practice for our clients, and ideate ways to overcome the challenges that arise when clients’ wants are misaligned
- Interact with ML infrastructure to train, troubleshoot and deploy ML models
What we’re looking for:
- 1+ years’ experience in a professional environment, ideally within tech
- Strong problem solving skills
- Knowledge of SQL and Python and an interest in developing skills in these areas
- An analytical and data-driven mindset
- Impeccable attention to detail
- Proactivity and the ability to effectively prioritise
- Great time management skills and the ability to set and work to deadlines
- Strong communication skills and a love of working collaboratively
- Great internal and external stakeholder management skills and confidence when speaking to others
- You’re passionate about Machine Learning and have a genuine interest in NLP topics and pipelines
- You’re adaptable, resourceful, and comfortable working in the exciting and ambiguous environment of a startup
Why join us?
- A competitive salary as well as the ability to share in the company’s success through options
- We want you to grow with us, so we place huge importance on providing our people with great opportunities to develop and progress, such as a £500 (yearly) personal development budget, a progression framework, unlimited access to a fully stocked library and biweekly Breakfast and Learns
- Great progression opportunities - we want you to grow with us!
- A flexible Health & Wellness benefits budget that can be spent on health insurance, physical and mental health or other needs starting at £50pcm growing £25pcm for each year of service
- 25 days holiday (in addition to bank holidays) + 1 day for your birthday + 1 day for every year of service up to 5 years
- Perks including discounts on cinema tickets, utilities and more
- Flexible working conditions and the opportunity to work from home
- Lovely office with great classes, events, and a rooftop terrace (when not in a pandemic!)
- Regular company socials planned by our great colleagues!