Applied Scientist (Machine Learning) - #1777988

Hello! We're Teya.

Teya is a payment and software service provider, headquartered in London serving small, local businesses across Europe. Founded in 2019, we build easy to use, integrated tools that enable our members to accept payments and boost business performance.

At Teya we believe small, local businesses are the lifeblood of our communities.

We’re here because we don’t believe there’s a level playing field that gives small businesses with a fighting chance against the giants of the high street.

We’re here because we see banks and legacy service providers making things harder for them. We don’t think the best technology or the best service should be reserved for those with the biggest headquarters.

We’re here to fight for a future where small, local businesses can thrive, and to commit the same dedication they offer all of us.

Become a part of our story.

We’re looking for exceptional talent to join our mission. We offer a chance to create impact in a high-energy and connected culture, while benefiting from continuous learning opportunities, a supportive community which is proud to serve our mission, and comprehensive benefits.

Your Mission

You will be part of a joint team of machine learning engineers, data scientists, data analysts, and product managers building and evolving ML models, real-time systems, reports, and performing deep analysis of pricing, retention, and offer strategies.

Working with advanced predictive models, MLOps best practices, and scalable software systems, you will implement and evolve intelligent solutions to align Teya with the success of our customers.

In This Role, You’ll Be

• Helping Teya to use data to drive business decisions by implementing and continuously improving through experimentation advanced machine learning models.
• Working on projects including but not limited to customer lifetime value, churn propensity, forecasting, risk, cost-to-serve and cost-to-acquire modelling
• Building predictive models to a production level adopting best practices for coding, deployment, monitoring, and experimentation.
  
  

Your Story

• Background in a quantitative field (Computer Science, Mathematics, Machine Learning, AI, Statistics, Economics or equivalent)
• 5+ years of professional working experience
• Someone who thrives in the incremental delivery of high quality production systems
• Proficiency in Java, Python, SQL, Jupyter Notebook
• Experience with Machine Learning and statistical inference.
• Understanding of ETL processes and data pipelines and ability to work closely with Machine Learning Engineers for product implementation
• Ability to communicate model objectives and performance to business stakeholders
• Strong analytical and problem-solving skills
• Ability to think creatively and insightfully about business problems
• Nice to have:
• Proficiency with Snowflake
• Proficiency with Amazon SageMaker
• Proficiency with Docker and Kubernetes
  

The Perks

• We trust you, so we offer flexible working hours, as long it suits both you and your team;
• Physical and mental health support through our partnership with GymPass giving free access to over 1,500 gyms in the UK, 1-1 therapy, meditation sessions, digital fitness and nutrition apps;
• Our company offers extended and improved maternity and paternity leave choices, giving employees more flexibility and support;
• Cycle-to-Work Scheme;
• Health and Life Insurance;
• Pension Scheme;
• 25 days of Annual Leave (+ Bank Holidays);
• Office snacks every day;
• Friendly, comfortable and informal office environment in Central London.
  
  

Teya is proud to be an equal opportunity employer.

We are committed to creating an inclusive environment where everyone regardless of race, ethnicity, gender identity or expression, sexual orientation, age, disability, religion, or background can thrive and do their best work. We believe that a diverse team leads to better ideas, stronger outcomes, and a more supportive workplace for all.

If you require any reasonable adjustments at any stage of the recruitment process whether for interviews, assessments, or other parts of the application—we encourage you to let us know. We are committed to ensuring that every candidate has a fair and accessible experience with us.