Platform Data Scientist - Algorithmic Incentive Models
Full-time
London, United Kingdom • In office | Hybrid | Remote (UK only)
About GoGorilla
GoGorilla is the world's first performance marketing company built on financial technology. We've engineered a platform that hardwires client objectives into every campaign, ensuring transparent, auditable results that traditional agencies can't match. When our clients win, you win. You'll join a high-performance London team where your commercial impact directly shapes your career trajectory and financial rewards.
About the role
As a Platform Data Scientist, you will be at the heart of our FinTech platform. You will be responsible for designing, building, and optimising the algorithmic incentive models that drive our success-sharing culture. This is a highly technical and strategic role where you will have the opportunity to work on a unique and complex set of problems at the intersection of data science, economics, and human behaviour.
Day-to-day, you'll be working with large datasets, building statistical models, and running experiments to improve our incentive algorithms. This role requires a deep understanding of statistical modelling, a passion for data-driven decision making, and a desire to build something truly innovative.
Working pattern and flexibility
This is a mid-level role with a high degree of flexibility. You can choose to work from our central London office, adopt a hybrid approach, or work fully remotely from anywhere in the UK. We trust you to manage your own time and deliver against your objectives. Time tracking is required for remote work to ensure security and progress monitoring, which is an industry-standard practice.
Leadership trajectory
This is a mid-level role with a clear path to technical leadership. You'll start by mastering our data science stack and consistently delivering high-impact models, with the opportunity to progress to a Senior or Lead role within 18-24 months. Exceptional performers will have the chance to build and lead their own data science team.
What you will be doing
Design, build, and optimise the algorithmic incentive models that drive our success-sharing culture.
Work with large datasets to understand the drivers of performance and identify opportunities for improvement.
Build statistical models to predict performance and simulate the impact of changes to our incentive models.
Run experiments to test new incentive models and measure their impact on performance.
Collaborate with our engineering, product, and finance teams to implement and deploy your models.
Stay up-to-date on the latest trends and techniques in data science and algorithmic game theory.
What you will bring
A strong background in statistics, econometrics, or a related quantitative field.
Expertise in statistical modelling and machine learning, with a deep understanding of techniques like regression, classification, and causal inference.
Proficiency in Python or R, and experience with data science libraries like pandas, scikit-learn, and statsmodels.
Experience with SQL and working with large datasets.
Right to work in the UK. We do not offer visa sponsorship.
A willingness to learn and a coachable mindset.
You should not apply if
You are not passionate about data science and its application to real-world problems.
You are not a creative problem-solver who enjoys tackling complex and ambiguous challenges.
You are not a team player who is willing to collaborate with others to achieve common goals.
You are not interested in a role that requires continuous learning and improvement.
You are not comfortable with a role that has a high degree of accountability for the performance of your models.
How we work
Outcomes first – your success is measured by the impact your models have on our business and our clients.
Autonomy with accountability – you have the freedom to manage your own research and development process with clear expectations for results.
Build the playbook – you will contribute to our data science playbook by developing and refining our modelling process and best practices.
Be the expert – you will be the go-to person for all things related to algorithmic incentive models.
Continuous improvement – feedback and data-driven insights shape our modelling process and drive continuous innovation.
Compensation and progression
Base salary: £50,000 to £65,000 (London), with adjustments for other UK locations (£45,000 to £60,000).
On-target performance bonus: Significant performance bonuses and success-sharing opportunities.
Company profit-sharing: Participation in overall company success.
Equity: Meaningful equity participation is a core part of our compensation philosophy for high-performing team members, offering a stake in our long-term success.
Benefits: Private healthcare for full-time UK employees after 6 months probation, 25 days holiday plus bank holidays, laptop and modern tools, learning budget and regular team events.
Progression: Clear path to Senior or Lead role within 18-24 months, with opportunities to build and lead your own data science team.
30-60-90 day expectations
Day 30 – Complete onboarding, learn our data science stack, and begin exploring our data.
Day 60 – Take ownership of your first modelling project and begin contributing to our data science playbook.
Day 90 – Consistently delivering high-impact models and demonstrating a clear impact on our business.
Our hiring process
We keep the steps simple so you can demonstrate how your skills drive outcomes and align with our culture. For this role, the journey usually follows our standard path – application, a short cultural profile, a light role task if applicable, interviews, offer and onboarding. See the careers page for specifics.
Typical flow for this role
Application – submit your CV and a short note on your experience with statistical modelling.
Cultural assessment – brief values and collaboration profile, plus short video questions.
Role task – a data science challenge to assess your skills and creative thinking.
Interviews – meet the hiring lead and other members of the data science team.
Offer and checks – written offer with base, bonus, and equity structure, right-to-work and references.
Onboarding – a clear plan, team introductions and access to all company resources.
Important notes for candidates
We do not use third-party recruitment agencies. Do not send CVs through agencies.
Apply only through our official channels. We will never ask for payment or personal financial information during the hiring process.
Double-check sender domains in email communications.
By applying, you confirm that the information is accurate and understand that employment is subject to right-to-work checks and references.
We process candidate data in line with our privacy notice.
