At a Glance
- Tasks: Lead the design of evaluation frameworks and improve customer experience through data analysis.
- Company: Wise, a global tech company revolutionising money management.
- Benefits: Competitive salary, diverse culture, and opportunities for professional growth.
- Other info: Embrace autonomy in a fast-paced environment with excellent career advancement potential.
- Why this job: Join a dynamic team to shape the future of automated customer support.
- Qualifications: Experience in data science, A/B testing, and strong communication skills required.
The predicted salary is between 80000 - 100000 € per year.
Wise is a global technology company building the best way to move and manage the world’s money.
We’re looking for a Data Science Lead to join our Contact Automation team in London.
About the Role
In the Support squad we aim to create a system that can power an automated “Wise Assistant” system that can answer most customer questions within the chat interface effectively, and support our agents in answering more complex questions. We need to apply this system effectively at scale across the majority of our contacts working seamlessly within the chat interface.
How You’ll Be Contributing
- Evaluation & Experimentation (Core Focus)
- Own the design and evolution of evaluation frameworks for LLM-based systems (both offline and online).
- Build and scale A/B testing to measure real customer impact and guide product decisions.
- Define meaningful metrics that connect system performance to customer outcomes and business impact.
- System Performance & Reliability
- Identify failure modes across the assistant (reasoning, retrieval, tool use, tone, etc.) and drive improvements.
- Work closely with engineers to iterate on agentic workflows.
- Continuously improve system behaviour through prompt design, evaluation insights, and data-driven iteration.
- Ensure the system performs reliably across multiple languages and geographies.
- Opportunity Identification
- Analyse conversation data to uncover new opportunities for improving the customer experience.
- Proactively shape what we should build next.
- Bring clarity to ambiguous problem spaces and turn them into actionable changes to the system.
- Cross-functional Collaboration
- Work daily with Product, Engineering, and Content/Design to shape the assistant’s behaviour.
- Influence decisions about the product through clear communication, data visualisations, and well-structured impactful proposals.
- Ensure the system is not only accurate, but intuitive and trustworthy from a customer perspective.
How You’ll Work
You will operate with a high degree of autonomy in a fast-moving environment (often working on 1–2 week iteration cycles) in close collaboration with engineering, content and product. Use feedback loops—both human and system-generated—to continuously improve performance. Take ownership beyond your immediate scope when needed to move the project forward.
Qualifications
- Strong sense of ownership; you drive work from idea to production and are motivated by building real systems used by customers.
- Good communicator, you are able to present ideas and foster discussion with both technical and non-technical audiences.
- Strong grounding in statistics, with the ability to design, run and own A/B testing and experimentation end-to-end.
- Strong understanding of how to evaluate models (classification, regression, or LLMs) and why metrics matter and a proven ability to connect model/system performance to business outcomes.
- A strong product mindset and ability to work collaboratively in a cross-functional environment.
- Experience writing production code in at least one of Python, TypeScript or Java.
- Familiarity with modern LLM/agentic architectures (e.g. Mastra, LangGraph or similar frameworks).
- Strong data skills (SQL, Snowflake, data visualisation).
Skills
Some extra skills that are great (but not essential).
- Experience with a customer-facing agentic system.
- Experience with Bayesian inference, especially with A/B testing.
Additional Information
We are committed to diversity and inclusion. If you’re passionate about learning and want to join our mission, we’d like to hear from you.
Lead Data Scientist - Contact Automation employer: hackajob
Wise is an exceptional employer that fosters a dynamic and inclusive work culture, particularly in our London office where the Lead Data Scientist will thrive. We offer competitive benefits, opportunities for professional growth, and the chance to work on innovative projects that directly impact customer experience. Join us to be part of a collaborative team that values autonomy and creativity, making meaningful contributions to the future of financial technology.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data Scientist - Contact Automation
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those at Wise. A casual chat can lead to opportunities that aren’t even advertised yet. Don’t be shy; we all love a good conversation!
✨Tip Number 2
Show off your skills! If you’ve got a portfolio or any projects related to data science, make sure to highlight them during interviews. We want to see how you think and solve problems, so bring your A-game!
✨Tip Number 3
Prepare for those tricky questions! Brush up on your statistics and A/B testing knowledge, as they’re key for this role. We recommend practicing with friends or using mock interviews to get comfortable.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team at Wise. Let’s make it happen!
We think you need these skills to ace Lead Data Scientist - Contact Automation
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the Lead Data Scientist role. Highlight your experience with A/B testing, data analysis, and any relevant projects that showcase your ability to drive systems from idea to production.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about the role and how your background aligns with our mission at Wise. Share specific examples of your work in data science and how you've contributed to improving customer experiences.
Showcase Your Communication Skills:Since you'll be collaborating with various teams, it's crucial to demonstrate your ability to communicate complex ideas clearly. Use your application to show how you've successfully worked with both technical and non-technical audiences in the past.
Apply Through Our Website:We encourage you to apply directly through our website. This way, we can ensure your application gets the attention it deserves and you can easily keep track of your application status!
How to prepare for a job interview at hackajob
✨Know Your Data Science Stuff
Make sure you brush up on your statistics and A/B testing knowledge. Be ready to discuss how you've designed experiments in the past and how you can connect model performance to real business outcomes. This role is all about evaluation and experimentation, so show them you know your stuff!
✨Show Off Your Communication Skills
Since you'll be working with both technical and non-technical teams, practice explaining complex concepts in simple terms. Prepare examples of how you've influenced product decisions through clear communication and data visualisations. They want to see that you can bridge the gap between different teams.
✨Be Ready for Problem-Solving
Think about some ambiguous problem spaces you've tackled before. Be prepared to discuss how you identified opportunities for improvement and turned them into actionable changes. This shows your proactive mindset and ability to drive work from idea to production.
✨Familiarise Yourself with Their Tech Stack
Get to know the tools and technologies mentioned in the job description, like Python, TypeScript, or Java, as well as LLM architectures. If you have experience with customer-facing systems, make sure to highlight that. Showing familiarity with their tech stack will give you an edge!
