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- Tasks: Architect and develop cutting-edge fraud detection systems using AI/ML.
- Company: Join SheerID, a leader in secure, data-driven marketing.
- Benefits: Competitive salary, inclusive culture, and opportunities for professional growth.
- Other info: Dynamic team environment focused on innovation and continuous learning.
- Why this job: Make a real impact by safeguarding our platform and mentoring future leaders.
- Qualifications: 20+ years in data science with expertise in fraud analytics and machine learning.
The predicted salary is between 80000 - 100000 £ per year.
Make a real difference with your engineering and analytical skills. At SheerID, we're building the future of secure, data-driven marketing with our innovative Audience Data Platform. Our mission is to deliver a seamless verification experience for millions of users monthly, ensuring that exclusive offers reach the right people while proactively identifying and neutralizing sophisticated fraud.
As a Principal Data Scientist, you'll play a critical role in architecting, developing, and deploying cutting-edge fraud detection and prevention systems within our SaaS solutions. You will have a direct impact on SheerID’s growth by safeguarding the integrity of our platform. You’ll collaborate with a high-performing team to build scalable, real-time models that distinguish between genuine users and bad actors. You'll not only build sophisticated defense systems but also mentor colleagues, conduct technical reviews, and lead the charge in staying ahead of evolving fraud tactics.
We're seeking a passionate and experienced data science leader with a deep foundation in anomaly detection, pattern recognition, and machine learning. You thrive in collaborative environments, possess strong leadership qualities, and are committed to crafting high-quality, secure software that protects our clients and their customers from digital deception.
Role Specific Job Duties- Architect Fraud Solutions: Partner with product & engineering to design and implement high-performance, scalable AI/ML models to detect and prevent fraud in data-intensive applications.
- Drive Innovation: Champion best practices and explore emerging technologies to enhance the fraud detection platform.
- Mentor and Lead: Provide technical leadership through architectural reviews and mentorship, fostering a culture of automation and continuous learning.
- Influence Strategy: Partner with product and engineering leadership to define the roadmap, balancing model scaling with reliability trade-offs.
- Solve Complex Challenges: Act as the technical escalation point for the "hairiest" problems, from data quality issues to model performance bottlenecks.
- Own the Lifecycle: Manage projects from design and development to deployment, monitoring, and post-mortem analysis.
- Collaborate Cross-Functionally: Translate complex business requirements and research into robust, production-ready AI solutions alongside engineers and product managers.
- Bachelor’s degree in Computer Science, Software Engineering, Statistics, Mathematics, or a related quantitative field (equivalent experience considered).
- 20+ years of relevant experience in data science, with a strong focus on predictive fraud analytics and large-scale data applications.
- Proven ability to design, develop, and deploy scalable and maintainable machine learning models in a production environment.
- Deep understanding of statistical methods, machine learning algorithms, and advanced data mining techniques.
- Proficiency in a statistical/general programming language (e.g., Python, R, Scala), with extensive experience with relevant libraries and frameworks.
- Expertise in debugging complex data issues and model performance problems.
- Exceptional communication, interpersonal, and problem-solving skills, with a demonstrated ability to influence and lead across teams.
- Strong foundational knowledge of data architecture/data warehousing and a track record of execution.
- Expertise with Big Data, Data Science, or Stream Processing techniques.
- Experience applying advanced AI models, including computer vision and deep learning, to solve real-world problems.
- Experience with AWS, Kubernetes, VertexAI, Labelbox, and MLOps practices.
- Experience with SQL and NoSQL databases (MongoDB, Elasticsearch, etc.).
- Experience with graph analysis and network science for fraud detection.
- Experience with automated data processing pipelines and feature engineering at scale.
SheerID is an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We celebrate diversity and are committed to creating an inclusive environment for all candidates and employees. SheerID believes that diversity and inclusion is critical to our success as a company, and we seek to recruit, develop and retain the most talented people from a diverse candidate pool.
Principal Data Scientist in London employer: SheerID Inc.
Contact Detail:
SheerID Inc. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Principal Data Scientist in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the data science field, especially those who work at SheerID or similar companies. A friendly chat can lead to insider info about job openings and even referrals.
✨Tip Number 2
Show off your skills! Prepare a portfolio showcasing your projects, especially those related to fraud detection and machine learning. This will give you an edge during interviews and demonstrate your hands-on experience.
✨Tip Number 3
Practice makes perfect! Brush up on your technical skills and be ready to tackle coding challenges or case studies during interviews. We recommend using platforms that simulate real-world problems to get you in the zone.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows your genuine interest in joining SheerID and being part of our mission to combat fraud.
We think you need these skills to ace Principal Data Scientist in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Principal Data Scientist role. Highlight your expertise in fraud detection, machine learning, and any relevant projects you've worked on. We want to see how you can make a real difference!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to tell us why you're passionate about data science and how your background makes you the perfect fit for our team. Don't forget to mention your leadership experience and collaborative spirit!
Showcase Your Projects: If you've worked on any interesting projects related to fraud detection or machine learning, be sure to include them in your application. We love seeing practical examples of your work and how you've tackled complex challenges in the past.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows us you're keen to join our innovative team at SheerID!
How to prepare for a job interview at SheerID Inc.
✨Know Your Stuff
Make sure you brush up on your knowledge of machine learning algorithms and anomaly detection techniques. Be ready to discuss specific projects where you've implemented these skills, as well as the challenges you faced and how you overcame them.
✨Showcase Your Leadership
As a Principal Data Scientist, you'll be expected to mentor others and lead projects. Prepare examples of how you've successfully led teams or mentored colleagues in the past. Highlight your ability to influence strategy and drive innovation within a team.
✨Understand Their Mission
Familiarise yourself with SheerID's mission and the importance of fraud detection in their Audience Data Platform. Be prepared to discuss how your experience aligns with their goals and how you can contribute to safeguarding their platform.
✨Ask Insightful Questions
Prepare thoughtful questions that demonstrate your interest in the role and the company. Inquire about their current challenges in fraud detection, the technologies they are exploring, and how they envision the future of their data-driven marketing efforts.