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Data Scientist - Credit Risk Modelling

Data Scientist - Credit Risk Modelling

Hybrid in London

We’re looking for a Data Scientist

Our credit models are central to our lending strategy at iwoca. They are already highly developed for our lending today, but we want to go further tomorrow. As a Data Scientist in our team, you will work directly on advancing these models, possibly by incorporating techniques from the statistics and machine learning literature, in order to support our future lending strategy and product development. This is an opportunity to work at the heart of risk modelling within our business.

The company

Fast, flexible finance empowers small businesses to manage their cash flow better and seize opportunities - making their business and the economy stronger as a whole. At iwoca, we do just that. We help businesses get the funds they need, when they need it, often within minutes. We’ve already made several billion in funding available to more than 100,000 businesses since we launched in 2012, and positioned ourselves as a leading Fintech in Europe. 

Our mission is to finance one million businesses. We’ll get there by continuing to make our finance ever more relevant and accessible to more businesses by combining cutting-edge technology, data science, and a 5-star customer service. 

The team

Our team is a versatile group of data scientists, engineers, and credit risk experts. They manage our lending strategy in terms of credit decisions and loss rates and develop our credit models, right from the R&D stage all the way to deploying models into production. We are a full-stack team, managing our down data processing and deployments, but with substantial collaboration with other tech teams and areas of the business.

The team also owns our customer lifetime value (CLtV) model, another highly tailored mathematical model which is used for optimisation throughout the business.

Our dynamic and autonomous environment emphasises ‘getting things done’ and delivering high quality solutions. You can expect to work closely with stakeholders, delivering solutions iteratively to incrementally add value, collecting and addressing feedback, and also providing support to the team and wider business.

The role

Your role as a Data Scientist will involve growing and demonstrating your skills in several key areas, including but not limited to:

  • Model development.

    • Explore and integrate innovative modelling methods into our training pipeline to enhance the predictive power and flexibility of our models.

    • Take responsibility for the full lifecycle of the model, including training, validation, deployment, and performance monitoring.

    • Clearly communicate and explain any model changes to the business, ensuring transparency and fostering trust in the model's predictions.

    • Collaborate with Data Scientists and Analysts in other teams to ensure that our model predictions are appropriately utilised and interdependencies are accounted for.

  • Model-driven insights.

    • Utilise our modelling and analytics tools (and introduce new ones where appropriate) to uncover insights, such as customer behaviour patterns, features predictive of lending outcomes, or the efficacy of new modelling techniques.

    • Effectively communicate these insights with the broader business to drive value by informing our lending strategy.

  • Project ownership and autonomy.

    • Independently develop data science solutions to address iwoca's challenges in credit risk and customer lifetime value modelling, with increasing responsibility in solution design.

    • Maintain strong communications with stakeholders throughout your work to ensure that your solutions are pragmatically solving the business problem at hand and to get technical feedback for personal growth.

The requirements

Essential:

  • Ability to effectively communicate with stakeholders and downstream users of the model, and to maintain up-to-date and reliable documentation.

  • Strong problem-solving skills in probability and statistics

  • Experience developing code collaboratively and implementing solutions in a production environment.

  • Proficiency with data manipulation and modelling tools, e.g., pandas, statsmodels, R.

  • Experience with scientific computing and tooling, e.g., NumPy, SciPy, Matlab, etc.

  • Self-driven with the capability to efficiently manage projects end-to-end.

  • Experience working on research projects, particularly those involving mathematical, statistical, or analytical modelling.

  • Experience building machine learning models from scratch (e.g., built your own optimiser).

  • Experience with Python or ability to pick this up quickly. (Note: we mostly work in Python.)

Bonus:

  • Excellent knowledge of stochastic processes and related mathematical techniques.

  • Knowledge of financial concepts (e.g. calculations with deterministic cash flows).

The salary

We expect to pay from £60,000 - £80,000 for this role. But, we’re open-minded, so definitely include your salary goals with your application. We routinely benchmark salaries against market rates, and run quarterly performance and salary reviews. 

The culture

At iwoca, we prioritise a culture of learning, growth, and support, and invest in the professional development of our team members. We value thought and skill diversity, and encourage you to explore new areas of interest to help us innovate and improve our products and services.

The offices

We put a lot of effort into making iwoca a great place to work:

  • Offices in London, Leeds, Frankfurt, and Berlin with plenty of drinks and snacks.

  • Events and clubs, like bingo, comedy nights, yoga classes, football, etc.

The benefits

  • Medical insurance from Vitality, including discounted gym membership. 

  • A private GP service (separate from Vitality) for you, your partner, and your dependents.

  • 25 days’ holiday, an extra day off for your birthday, the option to buy or sell an additional five days of annual leave, and unlimited unpaid leave. 

  • A one-month, fully paid sabbatical after four years.

  • Instant access to external counselling and therapy sessions for team members that need emotional or mental health support.

  • 3% pension contributions on total earnings.

  • An employee equity incentive scheme. 

  • Generous parental leave and a nursery tax benefit scheme to help you save money.

  • Electric car scheme and cycle to work scheme.

  • Two company retreats a year, we’ve been to France, Italy, Spain, and further afield.

And to make sure we all keep learning, we offer:

  • A learning and development budget for everyone.

  • Company-wide talks with internal and external speakers.

  • Access to learning platforms like Treehouse.

Useful links:

iwoca Glassdoor Company Review
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iwoca DE&I Review
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CEO of iwoca
iwoca CEO photo
Christoph Rieche
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Average salary estimate

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$60000K
$80000K

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What You Should Know About Data Scientist - Credit Risk Modelling, iwoca

As a Data Scientist specializing in Credit Risk Modelling at iwoca in London, you will play a pivotal role in shaping our lending strategy through advanced modelling techniques. iwoca is renowned for empowering small businesses with timely financial solutions, and your expertise will help us enhance our already sophisticated credit models. In this hybrid position, you'll leverage statistical and machine learning methods to drive our future product development. Collaborating with a dynamic team of data scientists, analysts, and credit risk experts, you'll manage every aspect of model development – from training and validation to deployment and monitoring. Your insights will be crucial in recognizing customer behavior patterns and improving lending outcomes. With a culture that encourages growth and innovation, iwoca offers a vibrant environment where your ideas can flourish. Enjoy a competitive salary while being part of a mission to finance a million businesses, facilitating their path to success. This role is not just about analytics; it’s about making a real impact on the economy by providing fast, flexible finance that helps businesses thrive. If you are a self-driven individual eager to tackle challenges in credit risk, and ready to communicate your innovative model-driven insights effectively across the business, iwoca is your perfect match! Here, we blend technology and a commitment to customer service in a workspace that’s lively and supportive.

Frequently Asked Questions (FAQs) for Data Scientist - Credit Risk Modelling Role at iwoca
What roles and responsibilities does the Data Scientist - Credit Risk Modelling at iwoca involve?

As a Data Scientist specializing in Credit Risk Modelling at iwoca, your responsibilities will include model development, integrating innovative methods to enhance predictive accuracy, taking ownership of the full lifecycle of models, and clearly communicating changes to stakeholders. You'll collaborate with various teams to ensure our models are effectively utilized, and through your insights, help inform our lending strategies.

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What qualifications are needed for the Data Scientist - Credit Risk Modelling role at iwoca?

To qualify for the Data Scientist - Credit Risk Modelling position at iwoca, you should possess strong problem-solving skills in probability and statistics, experience with coding in collaborative environments, and proficiency in data manipulation tools like pandas and R. Experience with scientific computing, such as NumPy and SciPy, is also essential, along with a proven track record of building machine learning models.

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What kind of experience is beneficial for a Data Scientist - Credit Risk Modelling at iwoca?

Beneficial experience for the Data Scientist - Credit Risk Modelling role at iwoca includes working on research projects involving mathematical and statistical modeling, building machine learning models from the ground up, and familiarity with financial concepts. A strong grasp of stochastic processes and statistical tools will also enhance your profile.

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What is the work culture like for a Data Scientist at iwoca?

The work culture for a Data Scientist at iwoca is centered around learning and growth. We prioritize teamwork and innovative thinking, where every member's contributions are valued. You will have the opportunity to explore new areas and enhance your skills, while also taking part in fun events and a supportive work environment that encourages professional development.

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What are the benefits of working as a Data Scientist - Credit Risk Modelling at iwoca?

Working as a Data Scientist - Credit Risk Modelling at iwoca comes with a host of benefits, including medical insurance, generous annual leave, a robust pension scheme, equity incentives, and wellness programs. Additionally, you’ll enjoy a supportive environment focused on learning and personal development, making it a great place to further your career.

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Common Interview Questions for Data Scientist - Credit Risk Modelling
Can you explain your process for model development in credit risk?

When developing models for credit risk, I follow a structured process that includes defining objectives, gathering relevant data, exploratory data analysis, building initial models, refining through testing and validation, deploying the model, and monitoring its performance post-deployment. This iterative approach helps to ensure the model meets business needs effectively.

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How do you handle model validation and performance monitoring?

For model validation, I use techniques like cross-validation and holdout datasets to ensure the model generalizes well. Performance monitoring involves setting key performance indicators (KPIs) and continuously assessing the model against these benchmarks, making adjustments as necessary to maintain accuracy and reliability.

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What techniques do you implement to improve predictive accuracy in your models?

To enhance predictive accuracy, I explore innovative modelling methods, such as ensemble techniques or incorporating neural networks, and optimize feature selection to focus on the most relevant data points. Continuous refinement based on feedback from model performance also plays a significant role.

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Can you give an example of a challenging data science project you've worked on?

One challenging project involved developing a customer lifetime value model from scratch. This required extensive data collection, creative problem-solving to identify factors impacting value, and close collaboration with marketing teams to ensure insights were correctly interpreted and applied, leading to significant improvements in strategy.

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What experience do you have with stakeholder communication?

I prioritize clear communication with stakeholders by providing accessible updates on model developments and changes. I often use visualizations and presentations to convey complex concepts simply, ensuring alignment and building trust in the model's outcomes.

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How do you keep up with advancements in data science and machine learning?

To stay updated, I regularly read industry publications, participate in webinars, and enroll in relevant online courses. Additionally, I engage with the data science community through forums and attend conferences, allowing me to learn and apply new trends and technologies.

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What programming languages and tools do you prefer for data manipulation?

I primarily use Python with libraries like pandas and NumPy for data manipulation due to their efficiency and flexibility. However, I also have experience with R and can quickly adapt to any tools or languages required for the job.

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How do you approach working on collaborative projects within a team?

In collaborative projects, I focus on open communication and actively seek feedback from my teammates. I ensure that everyone is aligned on project goals and timelines, and I value contributions from all team members to foster a constructive and inclusive work environment.

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What methods do you use to identify customer behavior patterns?

I utilize exploratory data analysis techniques and machine learning methods like clustering and decision trees to uncover customer behavior patterns. By analyzing transaction data, I can derive insights that help in tailoring our lending strategies and enhancing customer engagement.

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Can you explain your experience with machine learning models?

I have extensive experience building and implementing various machine learning models, including regression, classification, and clustering techniques. My expertise ranges from developing models from scratch to fine-tuning pre-existing models to better fit business requirements and improve prediction outcomes.

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iwoca allows small businesses to access the type of short-term funding previously only available to their larger peers. From taking advantage of new trade opportunities to bridging cashflow gaps, we believe flexible access to finance is crucial to...

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