Senior Data Scientist - US Products

Lendable is on a mission to build the world's best technology to help people get credit and save money. We're building one of the world’s leading fintech companies and are off to a strong start:

• One of the UK’s newest unicorns with a team of just over 700 people

• Among the fastest-growing tech companies in the UK

• Profitable since 2017

• Backed by top investors including Balderton Capital and Goldman Sachs

• Loved by customers with the best reviews in the market (4.9 across 10,000s of reviews on Trustpilot)

So far, we’ve rebuilt the Big Three consumer finance products from scratch: loans, credit cards and car finance. We get money into our customers’ hands in minutes instead of days.

We’re growing fast, and there’s a lot more to do: we’re going after the two biggest Western markets (UK and US) where trillions worth of financial products are held by big banks with dated systems and painful processes.

1. Take ownership across a broad remit. You are trusted to make decisions that drive a material impact on the direction and success of Lendable from day 1

2. Work in small teams of exceptional people, who are relentlessly resourceful to solve problems and find smarter solutions than the status quo

3. Build the best technology in-house, using new data sources, machine learning and AI to make machines do the heavy lifting

We are excited to be hiring a new Senior Data Scientist for our team! Ideally, this role will suit someone with a proven background in building models ideally in credit, lending, or other areas of financial services. Lendable is the market leader in real rate risk-based pricing, offering consumers transparency and product assurance at the point of application. Data Science sits at the heart of this USP, developing the credit risk models to underwrite loan and credit card products.

You will have access to the latest machine learning techniques combined with a rich data repository to deliver best in market risk models.

This role will primarily focus on our US unsecured loans and credit cards business.

Our team’s objectives

• The data science team develops proprietary machine learning models combining state-of-the-art techniques with a variety of data sources that inform scorecard development and risk management, optimise marketing and pricing, and improve operations efficiency.

• Research new data sources and unstructured data representation.

• Data scientists work across the business in a multidisciplinary capacity to identify issues, translate business problems into data questions, analyse and propose solutions.

• Deliver data services to a wide variety of stakeholders by engineering CLI programs / APIs.

• Design, implement, manage and evaluate experiments of products and services leading to constant innovation and improvement.

How you’ll impact those objectives

• Use your expertise to build and deploy models that contribute to the success of the business.

• Stay up to date with the latest advancements in machine learning and credit risk modelling proactively proposing new approaches and projects that drive innovation.

• Learn the domain of products that Lendable serves, understanding the data that informs strategy and risk modelling.

• Extract, parse, clean and transform data for use in machine learning.

• Clearly communicate results to stakeholders through verbal and written communication.

• Mentor other data scientists and promote best practices throughout the team and business.

Key Skills

• Knowledge of machine learning techniques and their respective pros and cons.

• Ability to communicate sophisticated topics clearly and concisely.

• Proficiency with creating ML models in Python with experiment tracking tools, such as MLFlow.

• Curiosity, creativity, resourcefulness and a collaborative spirit.

• Interest in problems related to the financial services domain - a knowledge of loan or credit card underwriting is advantageous.

• Confident communicator and contributes effectively within a team environment.

• Experience mentoring or leading others.

• Self-driven and willing to lead on projects / new initiatives.

Familiarity with data used within credit risk decisioning such as Credit Bureau data, especially across multiple geographies is an advantage.

The interview process

We’re not corporate, so we try our best to get things moving as quickly as possible. For this role, we’d expect:

• A quick phone call with the people team

• Interview with hiring manager

• Take home task

• Task debrief

• Case study interview

• In person interview where you'll do your final round and have some lunch with the team

• Winning team: the opportunity to scale up one of the world’s most successful fintech companies

• Flexible working: flexible approach tailored to each role. Hybrid roles require three days in-office weekly; fully remote roles include regular opportunities for in-person connection through socials and off-sites

• Socials & connection: opportunities and events to come together, socialise, and get to know each other beyond the office walls

• Health coverage: support for your physical and mental wellbeing, including private health cover

• Retirement & savings: long-term financial wellbeing through retirement savings plans

• Employee referral programme: earn a competitive bonus when you refer successful new team members

• Office meals & snacks: enjoy a fully stocked kitchen, plus complimentary lunches prepared by in-house chefs on in-office days at select locations

• Sustainable commuting: cycle-to-work and electric vehicle salary sacrifice schemes available in select locations

Please note: The availability and details of specific benefits vary by location and role. For more information, please speak to your Talent Partner.

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