At a Glance
- Tasks: Use data analytics and machine learning to drive lead generation in the payments industry.
- Company: Join a forward-thinking company in London with a focus on innovation.
- Benefits: Enjoy a competitive salary, community support time, and global recognition.
- Other info: Fast-paced environment with opportunities for personal and professional growth.
- Why this job: Make an impact by optimising marketing strategies with cutting-edge data insights.
- Qualifications: Experience in data science, Python, SQL, and machine learning is essential.
The predicted salary is between 60000 - 80000 £ per year.
Location: London hub.
Responsibilities
- Utilize advanced data analytics and machine learning techniques to identify high‑value prospects and generate leads in the payments industry.
- Design and implement propensity models to predict potential client engagement and conversion rates, optimizing prospecting strategies.
- Analyze transactional and financial data to uncover trends and insights that inform targeted marketing and sales strategies.
- Identify and evaluate new data sources (internal and external) to support and drive improvements in predictive models.
- Work closely with the marketing and sales teams to refine lead qualification processes, enhance lead scoring models, and streamline lead generation efforts.
- Develop and maintain Python/SQL‑based automated workflows for efficient data preparation, modelling and execution of marketing/prospecting strategies.
- Present data‑driven insights and recommendations to stakeholders to drive strategic decisions and new business initiatives.
- Continuously monitor the effectiveness of lead generation strategies and adjust models and approaches based on performance data and market feedback.
Qualifications
- Proven experience in data science with a focus on targeted marketing, lead generation and new business development.
- Expertise in Python and SQL, with experience in data preparation, cleaning and modelling.
- Experience building and deploying machine learning models, especially related to customer behaviour, segmentation and propensity analysis.
- Excellent analytical and problem‑solving abilities, with a track record of translating data insights into successful business outcomes.
- Entrepreneurial mindset with the ability to operate in a fast‑paced environment and manage multiple projects with varying deadlines.
- Bachelor’s or master’s degree in Statistics, Mathematics, Computer Science, Finance or a related field.
- Desirable (not required):
- Experience working in a Snowflake platform environment.
- Experience with APIs.
- Experience integrating data solutions with Salesforce CRM.
Benefits
- Competitive salary and benefits.
- Time allocated to support charities and give back to the community.
- Parental leave policy.
- Global recognition platform.
- Access to Virgin Pulse.
- Global employee assistance program.
Senior Data Scientist/Engineer - Commercial Optimisation employer: Worldpay (UK) Limited
As a Senior Data Scientist/Engineer in our London hub, you will thrive in a dynamic work culture that champions innovation and collaboration. We offer competitive salaries, generous parental leave, and dedicated time for community engagement, ensuring that our employees not only excel professionally but also contribute meaningfully to society. With ample opportunities for growth and development, you will be empowered to leverage your expertise in data analytics and machine learning to drive impactful business strategies in the payments industry.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Scientist/Engineer - Commercial Optimisation
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. We all know that sometimes it’s not just what you know, but who you know that can help you land that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data projects, especially those involving Python and SQL. We recommend sharing your work on platforms like GitHub or even your own website to make it easy for recruiters to see what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and understanding the latest trends in data science. We suggest practising common interview questions and even doing mock interviews with friends to build your confidence.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Senior Data Scientist/Engineer - Commercial Optimisation
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the role of Senior Data Scientist/Engineer. Highlight your experience with data analytics, machine learning, and any relevant projects that showcase your skills in Python and SQL.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're the perfect fit for this role. Share specific examples of how you've used data to drive business decisions and how you can contribute to our team’s success in commercial optimisation.
Showcase Your Analytical Skills:In your application, don’t just list your skills—demonstrate them! Include examples of how you've built and deployed machine learning models or improved lead generation strategies in previous roles.
Apply Through Our Website:We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Worldpay (UK) Limited
✨Know Your Data Inside Out
Make sure you’re well-versed in the data analytics and machine learning techniques relevant to the role. Brush up on your Python and SQL skills, and be ready to discuss how you've used these tools to drive successful marketing strategies in the past.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled complex data challenges before. Think about specific instances where your analytical abilities led to actionable insights that improved lead generation or client engagement.
✨Understand the Business Context
Familiarise yourself with the payments industry and the company’s position within it. Be prepared to discuss how your experience can help refine lead qualification processes and enhance lead scoring models tailored to their needs.
✨Engage with Stakeholders
Since presenting data-driven insights is key, practice how you would communicate your findings to non-technical stakeholders. Use clear, concise language and be ready to explain the impact of your recommendations on strategic decisions.
