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For Companies At a Glance
- Tasks: Develop ML models, analyse data, and mentor junior team members in a dynamic FinTech environment.
- Company: Join a cutting-edge FinTech revolutionising payment solutions with data-driven innovation.
- Benefits: Enjoy hybrid work options, competitive salary, and opportunities for professional growth.
- Why this job: Make a real impact in the payments landscape while collaborating with diverse teams.
- Qualifications: Bachelor’s, Master’s, or PhD in relevant fields; experience in data science and graph analytics required.
- Other info: Work with advanced technologies like Spark and cloud platforms, contributing to ethical AI practices.
The predicted salary is between 48000 - 84000 £ per year.
A FinTech specialising in cloud based payment solutions is looking for an experienced Senior Data Scientist to join their growing team in London. This innovative organisation is transforming the payments landscape by delivering seamless, data driven solutions for businesses worldwide. This is an opportunity to work on impactful projects, leveraging advanced data science techniques to optimise payment processing, detect anomalies, and improve operational efficiency. If you’re passionate about applying your skills in data science to drive innovation in payments, this role is for you.
What You’ll Be Doing
- Developing ML models to optimise payment workflows, detect anomalies, and predict payment success rates.
- Applying graph analytics techniques to uncover hidden relationships in transaction data and improve fraud detection mechanisms.
- Building and maintaining scalable data pipelines to support real time and batch processing of payment data.
- Leveraging Spark for distributed data processing and ML on large datasets.
- Collaborating with cross functional teams, including product, engineering, and operations, to translate business needs into data-driven solutions.
- Conducting deep statistical analysis and modelling to generate actionable insights for improving the payment platform.
- Mentoring junior team members and championing best practices in data science, including explainable AI and ethical model design.
What They’re Looking For
- Education: Bachelor’s, Master’s, or PhD in Computer Science, Statistics, Mathematics, Physics, or a related field.
- Experience: Professional experience in data science and graph analytics, preferably in the financial or payments industry.
- Expertise: Strong understanding of graph databases, graph algorithms, and graph analytics techniques.
- Technical Skills: Proficiency in programming languages such as Python or R, with experience using Spark for large-scale data processing and machine learning.
- Communication: Excellent communication skills with the ability to explain complex models to technical and non-technical stakeholders alike.
- Collaboration: Proven ability to work collaboratively in both onsite and remote environments, contributing effectively to a distributed team.
Desirable Skills
- Experience with cloud platforms such as AWS or GCP.
- Familiarity with transaction data processing and anomaly detection techniques.
- Knowledge of deploying models into production using MLOps tools like MLflow or SageMaker.
Senior Data Scientist employer: intro
Contact Detail:
intro Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist
✨Tip Number 1
Familiarise yourself with the latest trends in data science and graph analytics, especially within the FinTech sector. This will not only help you understand the industry better but also allow you to engage in informed discussions during interviews.
✨Tip Number 2
Showcase your experience with machine learning models and data pipelines by preparing specific examples of projects you've worked on. Be ready to discuss how you optimised workflows or improved fraud detection mechanisms in previous roles.
✨Tip Number 3
Brush up on your communication skills, particularly in explaining complex data science concepts to non-technical stakeholders. Practice articulating your thought process clearly, as this is crucial for collaboration in cross-functional teams.
✨Tip Number 4
Network with professionals in the FinTech space, especially those who work with cloud-based payment solutions. Attend relevant meetups or webinars to connect with potential colleagues and gain insights into the company culture and expectations.
We think you need these skills to ace Senior Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data science and graph analytics, particularly in the financial or payments industry. Emphasise your proficiency in Python or R and any experience with Spark.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data science and how it can drive innovation in payments. Mention specific projects or experiences that demonstrate your ability to develop ML models and conduct statistical analysis.
Showcase Your Technical Skills: Include specific examples of your work with graph databases and algorithms. If you have experience with cloud platforms like AWS or GCP, make sure to mention it, as well as any familiarity with MLOps tools.
Prepare for Interviews: Be ready to discuss your previous projects in detail, especially those involving anomaly detection and payment processing. Practice explaining complex models in simple terms, as communication skills are crucial for this role.
How to prepare for a job interview at intro
✨Showcase Your Technical Skills
Be prepared to discuss your experience with programming languages like Python or R, and your proficiency in using Spark for data processing. Highlight specific projects where you've developed ML models or applied graph analytics techniques.
✨Demonstrate Your Problem-Solving Abilities
Expect to face scenario-based questions that assess your analytical thinking. Prepare examples of how you've optimised payment workflows or detected anomalies in past roles, showcasing your ability to drive innovation in payments.
✨Communicate Clearly
Practice explaining complex data science concepts in simple terms. You'll need to convey your ideas effectively to both technical and non-technical stakeholders, so clarity is key during the interview.
✨Emphasise Collaboration Experience
Since the role involves working with cross-functional teams, be ready to share examples of how you've successfully collaborated with product, engineering, and operations teams in previous positions. Highlight your adaptability in both onsite and remote environments.
