At a Glance
- Tasks: Build ML models to tackle fraud and optimise transaction risk.
- Company: Join Signifyd's innovative Applied Decision Science team.
- Benefits: Enjoy remote work flexibility and a supportive team culture.
- Other info: Collaborative environment with opportunities for professional growth.
- Why this job: Make a real impact in fraud detection while honing your data science skills.
- Qualifications: Experience in Python, Spark, and a passion for data-driven decision making.
The predicted salary is between 49500 - 60500 £ per year.
Signifyd's Applied Decision Science team builds production ML models to assess transaction risk and automate fraud detection.
This role partners with the merchant portfolio to optimize decisioning and reduce false positives.
You will write production and analytical Python code, work with Spark/Databricks on distributed pipelines, and contribute to experiments and model improvements in a remote-friendly environment.
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Impactful Fraud & Risk Data Scientist II — Remote employer: Signifyd
At Signifyd, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters collaboration and innovation. Our commitment to employee growth is evident through continuous learning opportunities and a supportive environment, making it an ideal place for professionals looking to make a meaningful impact in the e-commerce sector. Located in the UK, we provide competitive salaries and generous benefits, including discretionary time off, ensuring our team members feel valued and motivated.
StudySmarter Expert Advice🤫
We think this is how you could land Impactful Fraud & Risk Data Scientist II — Remote
✨Get Involved in Data Science Meetups
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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 Signifyd.
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We think you need these skills to ace Impactful Fraud & Risk Data Scientist II — Remote
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 Signifyd, 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 Signifyd. 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 Signifyd
✨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 Signifyd!
✨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.
