Data Scientist - Operations Strategy team

iwoca Deutschland
City of London
2 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist (Government)

Data Scientist - Renewable Energy

Data Scientist - Operations Strategy team

Join to apply for the Data Scientist - Operations Strategy team role at iwoca Deutschland.


Company

iwoca is on a mission to make small businesses thrive. Since 2012, we have revolutionised how these businesses access finance, turning a once lengthy, frustrating process into fast, flexible, and effective funding that works for modern businesses. With billions in funding across Europe, we provide one of the continent’s leading fintech innovations.


Location

Hybrid in London, UK. (Works out of London, Leeds, Berlin, and Frankfurt).


Function

iwoca’s data scientists specialise in supervised machine learning, statistical inference and exploratory statistics, focusing on tabular and time‑series data. Our Operations Strategy team builds statistical models and runs split tests to improve the efficiency and effectiveness of our Operations teams while maintaining exceptional customer service.


Team

Approximately 200 members of the Operations team work in London and Leeds. Our eight‑person Operations Strategy team aims to make customer‑facing teams more efficient and effective.


Role

As a Data Scientist in our Operations Strategy team, you will set up and analyse tests, build statistical models, and produce data‑driven insights that inform strategy and improve operational performance.


Strategy and Innovation

  • Work closely with the Head of Operations Strategy, Operations staff and other stakeholders to align work with business goals and achieve valuable commercial outcomes.
  • Design experiments to compare the performance of different strategies and evaluate them to inform decisions.
  • Share findings and models with the wider business to impact strategy.

Ownership and Influence

  • Independently build models to solve business problems, owning solution design.
  • Promote analytical rigor within the team, ensuring experimental designs are correctly defined and tests are evaluated without bias.
  • Data scientists play a key role in decision‑making, driving the data culture at iwoca.

Development Opportunities

  • Join our community of analysts, data scientists and statisticians for consistency in methodology across the organisation.
  • Build expertise in Operations processes across the full customer journey, from signup to collections.

Projects

  • Set up, monitor and analyse split tests to understand the value of operations activities, such as determining the ROI of outbound calls and prioritising them effectively.
  • Build predictive models based on customer satisfaction data to assess the impact of operational process changes.
  • Build statistical models to enhance forecasting and capacity planning for operations teams.

Essential

  • PhD in a relevant numerate discipline or proven experience solving business problems with statistics or machine learning.
  • Ability to dive deep into business context and translate data into actionable insights.
  • Strong problem‑solving skills in probability and statistics.
  • Proficiency with data manipulation and modelling tools (pandas, statsmodels, R).
  • Self‑driven with the capability to manage projects end‑to‑end.
  • Excellent communication skills, tailoring technical details to audience.

Bonus

  • Experience with Python (our primary language).
  • Experience with experimental design and Bayesian analysis.

Salary

£60,000 – £90,000 (open to discussion based on experience).


Culture

At iwoca, we prioritise a culture of learning, growth, and support, investing in professional development and encouraging diversity of thought.


Benefits

  • Flexible working hours.
  • Medical insurance via Vitality, gym membership discounts.
  • Private GP service for you and dependents.
  • 25 days holiday per year + extra birthday day + options to buy/sell additional leave.
  • One‑month fully paid sabbatical after four years.
  • Unlimited unpaid leave.
  • External counselling and therapy access.
  • 3% pension contributions.
  • Employee equity incentive scheme.
  • Generous parental leave and nursery tax benefit.
  • Electric car and cycle‑to‑work scheme.
  • Company retreats twice a year.
  • Learning and development budget for everyone.
  • Company‑wide talks with internal and external speakers.
  • Access to learning platforms (e.g., Treehouse).

Useful Links

  • iwoca benefits & policies
  • Interview welcome pack

Seniority level

Mid‑Senior level


Employment type

Full‑time


Job function

Engineering and Information Technology


#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.