At a Glance
- Tasks: Lead the development of credit risk models and drive data-driven decision making.
- Company: Fast-growing fintech company focused on innovative consumer lending solutions.
- Benefits: Competitive salary, hybrid working, bonus, pension, and private medical cover.
- Other info: Collaborative culture with clear career progression opportunities.
- Why this job: Shape credit risk strategy and make a real impact in a dynamic environment.
- Qualifications: Experience in consumer credit, strong programming skills in Python and SQL.
The predicted salary is between 60000 - 80000 £ per year.
This is an opportunity to step into a high impact Decision Science Lead role within a fast growing fintech environment. You will play a key role in shaping credit risk strategy through advanced analytics and machine learning, with strong exposure to senior stakeholders and clear progression opportunities.
The Company
They are a scaling fintech business operating in the consumer lending space, focused on delivering innovative, data driven solutions. With a strong market presence and growing customer base, they are competing with some of the largest players in the industry. The business combines a collaborative, agile culture with a clear ambition to continue expanding its analytics capability.
The Role
- Develop and enhance credit risk models including scorecards, behavioural, acquisition and fraud models
- Build predictive models using advanced statistical and machine learning techniques
- Deploy models into production using AWS SageMaker and collaborate with engineering teams
- Monitor model performance and ensure ongoing effectiveness across business and technical metrics
- Generate insights and present clear, actionable recommendations to stakeholders
- Explore new data sources and modelling approaches to drive innovation
- Work closely with cross functional teams to influence lending and risk decisions
Your Skills and Experience
- Strong commercial experience within consumer credit and lending environments
- Proven ability to develop credit risk models, including scorecards or predictive models
- Strong programming skills in Python and SQL with experience working in cloud environments such as AWS
- Solid grounding in statistics and machine learning
- Experience working with large, complex datasets and delivering business insights
- Strong communication skills with the ability to influence stakeholders
- Experience with model deployment is highly beneficial
- Exposure to dbt is desirable
What They Offer
- Salary between £70,000 and £90,000
- Hybrid working with two to three days in the office each week
- Competitive benefits package including bonus, pension and private medical cover
- Strong career progression opportunities within a growing data function
- A collaborative and supportive working environment with exposure to senior leadership
Decision Science Lead in Slough employer: Harnham
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StudySmarter Expert Advice🤫
We think this is how you could land Decision Science Lead in Slough
✨Get Involved in Data Science Meetups
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Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Decision Science Lead at Harnham.
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Harnham.
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We think you need these skills to ace Decision Science Lead in Slough
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Harnham, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Harnham. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Harnham
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Harnham!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
