Data Scientist (Marketing)
London, England, United Kingdom
Starling Bank
Transform the way you manage your money with Starling Bank. Enjoy personal and business banking online and at your fingertips, always. Apply in minutes.Starling is the UK’s first and leading digital bank on a mission to fix banking! Our vision is fast technology, fair service, and honest values. All at the tap of a phone, all the time.
We are about giving customers a new way to spend, save and manage their money while taking better care of the planet which has seen us become a multi-award winning bank that now employs over 2800 across five offices in London, Cardiff, Dublin, Southampton, and Manchester. Our journey started in 2014, and since then we have surpassed 3.5 million accounts (and four account types!) with 350,000 business customers. We are a fully licensed UK bank but at the heart, we are a tech first company, enabling our platform to deliver brilliant products.
Our technologists are at the very heart of Starling and enjoy working in a fast-paced environment that is all about building things, creating new stuff, and disruptive technology that keeps us on the cutting edge of fintech. We operate a flat structure to empower you to make decisions regardless of what your primary responsibilities may be, innovation and collaboration will be at the core of everything you do. Help is never far away in our open culture, you will find support in your team and from across the business, we are in this together!
The way to thrive and shine within Starling is to be a self-driven individual and be able to take full ownership of everything around you: From building things, designing, discovering, to sharing knowledge with your colleagues and making sure all processes are efficient and productive to deliver the best possible results for our customers. Our purpose is underpinned by five Starling values: Listen, Keep It Simple, Do The Right Thing, Own It, and Aim For Greatness.
Hybrid Working
We have a Hybrid approach to working here at Starling - our preference is that you're located within a commutable distance of one of our offices so that we're able to interact and collaborate in person. We don't like to mandate how much you visit the office and work from home, that's to be agreed upon between you and your manager.
We are looking for Data Scientists with experience working in Marketing to help the bank solve complex problems using Machine Learning. In this role, you'll use your skills and passion for data to understand our customers and drive growth through effective marketing strategies.
Responsibilites:
- Develop and refine models to predict customer lifetime value (LTV) to optimise marketing investments and resource allocation.
- Analyse customer behaviour and product usage data to identify target audiences and tailor marketing efforts for maximum impact.
- Employ causal models to evaluate the effectiveness of CRM and invite campaigns and use causal inference to personalise campaigns for individual users.
- Contribute to building and interpreting Marketing Mix Models (MMM) to understand the best growth activities.
- Collaborate with Data Analysts to ensure they effectively utilise the models you build.
Requirements
We’re open-minded when it comes to hiring and we care more about aptitude and attitude than specific experience or qualifications. We think the ideal candidate will encompass most of the following:
- Solid understanding of customer lifetime value (LTV) modelling and marketing mix modelling.
- Deep understanding of statistics, especially Bayesian reasoning, and the ability to assess the accuracy of your results.
- Experience with causal inference concepts and machine learning models for causal inference.
- Comfortable with a variety of modelling techniques, including gradient boosting, neural networks, linear regression, and blending these approaches.
- Expert in Python with the ability to make well-reasoned design decisions in your code.
- Comfortable working with external data sources through APIs.
- Ability to see the bigger picture of business processes and clearly define how models can be integrated and add value.
- Excellent communication and visualisation skills to effectively present your findings to different audiences.
Interview Process
Interviewing is a two way process and we want you to have the time and opportunity to get to know us, as much as we are getting to know you! Our interviews are conversational and we want to get the best from you, so come with questions and be curious. In general you can expect the below, following a chat with one of our Talent Team:
- Stage 1 - 45 mins with one of the team
- Stage 2 - Take home test
- Stage 3 - 60 mins technical interview with two team members
- Stage 4 - 45 min final with an executive and a member of the people team
Benefits
• 33 days holiday (including flexible bank holidays)
• An extra day’s holiday for your birthday
• 16 hours paid volunteering time a year
• Part-time and/or flexible hours available for most roles
• Salary sacrifice, company enhanced pension scheme
• Life insurance at 4x your salary
• Hybrid/remote working
• Private Medical Insurance with VitalityHealth including mental health support and cancer care. Partner benefits include discounts with Waitrose, Mr&Mrs Smith and Peloton
• Generous family-friendly policies
• Varied social groups set up and run by our employees
• Perkbox membership giving access to retail discounts, a wellness platform for physical and mental health, and weekly free and boosted perks
• Access to initiatives like Cycle to Work, Salary Sacrificed Gym partnerships and Electric Vehicle (EV) leasing
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: APIs Banking Bayesian Causal inference FinTech Machine Learning ML models Python Statistics
Perks/benefits: Career development Fitness / gym Flex hours Health care Home office stipend Team events Wellness
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