Senior Data Science Manager - Finance
Listed on 2026-02-27
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IT/Tech
AI Engineer, Data Science Manager, Machine Learning/ ML Engineer, Data Scientist
- Compensation: GBP 115,000 - GBP 150,000 - yearly
Wise is a global technology company, building the best way to move and manage the world’s money.
Min fees. Max ease. Full speed.
Whether people and businesses are sending money to another country, spending abroad, or making and receiving international payments, Wise is on a mission to make their lives easier and save them money.
As part of our team, you will be helping us create an entirely new network for the world's money.
For everyone, everywhere.
We are looking for an experienced detail-oriented Senior Data Science Manager to join our Financial Planning and Analysis (FP&A) team. This role will drive data analytics, build predictive models, and leverage machine learning to support strategic decision‑making across Wise.
With your team of (5) Data Scientists, you will partner closely with finance, operations, and product teams to uncover insights, forecast trends, and identify areas for operational efficiency and revenue growth.
This position offers a unique opportunity to influence business strategy by transforming complex datasets into actionable insights and enabling data‑driven decision‑making. What you and your team build will have a direct impact on Wise’s mission and millions of our customers worldwide.
Here’s how you’ll be contributing:
Technical Leadership & Innovation: Drive the technical vision for the time series forecasting and causal inference‑based models and pipelines. Making key decisions on technology adoption and guiding your team through complex technical challenges. You will also shape the research agenda and evaluate emerging AI/ML technologies for strategic adoption, fostering a culture of experimentation and continuous learning
Team Development & Mentorship: Lead, mentor, and grow our talented data scientists, building technical capabilities across the team, fostering career development, and promoting knowledge sharing on cutting‑edge technologies and methodologies.
Cross‑Functional Collaboration & Customer Impact: Partner strategically with Product, Engineering, and Operations leaders to embed data science effectively into product roadmaps. Strengthening a culture that prioritises tangible customer solutions and measurable impact over isolated experiments.
Delivery Excellence & Operationalisation: Establish and oversee scalable deployment strategies, robust MLOps practices, model monitoring, A/B testing, and performance tracking to ensure production success. Drive process improvements that accelerate iteration speed and delivery quality across all data science projects.
Organisational Impact: Define and enforce technical standards, model governance frameworks, and best practices across all data science projects. Drive process improvements that accelerate iteration speed and delivery quality
- Responsible AI Leadership: Champion ethical AI practices across the organization, establishing frameworks for bias mitigation and transparency while guiding the team in responsible AI development
WHAT YOU’LL BRING
Proven Leadership & Team Development: Experience leading high‑performing data science teams, driving the development of production‑grade Machine Learning and AI systems at scale, and delivering measurable business outcomes. Demonstrated ability to build, scale, mentor, hire, and grow both individual data scientists and data science leaders.
Deep Technical & AI/ML Expertise: Strong technical foundation with expertise in coding (Python, SQL), advanced modeling (Tree‑based, Neural Networks, Deep Learning), GenAI frameworks (Llama Index, Lang Graph, etc.), and cloud platforms (AWS, GCP, Azure). Proven ability to architect scalable solutions, design comprehensive data strategies, and guide technical decision‑making for complex AI/ML challenges and MLOps practices.
Domain Expertise: Experience in Financial Modeling & Forecasting. You have a deep understanding of financial planning processes, budgeting, variance analysis, and building predictive models for revenue, costs, and business performance metrics. Proficiency in time series analysis, econometric modeling, scenario planning, and statistical techniques for…
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