At a Glance
- Tasks: Monitor revenue, support partner analytics, and maintain production models with minimal supervision.
- Company: Award-winning global SaaS company with a collaborative and innovative culture.
- Benefits: Hybrid working, free breakfast, and potential for contract extension.
- Other info: Work cross-functionally and enjoy a supportive environment with career growth opportunities.
- Why this job: Join a dynamic team and make a real impact in data science and analytics.
- Qualifications: 5+ years in data science, strong SQL and Python skills, and excellent communication.
The predicted salary is between 63000 - 77000 £ per year.
Salary: £? - ? per year
Requirements
- 5+ years of experience in data science and analytics, including running production models and BAU analytics
- Proven ability to pick up existing BAU processes quickly and deliver with low to no supervision
- Strong SQL and Python or R skills; comfortable reading and maintaining an existing codebase and pipelines
- Hands-on experience maintaining production ML models, including refresh, retrain, monitor, and troubleshoot, rather than building from scratch
- Experience with model performance monitoring and data quality
- Excellent written and verbal communication skills
- Advanced degree in a quantitative discipline such as Computer Science, Mathematics, Statistics, Physics, or similar, or equivalent experience
- Preferred: experience using AI tools to automate day-to-day work and comfort with agentic workflows
- Preferred: prior contract or consulting experience delivering BAU to fixed timelines
- Preferred: comfortable working cross-functionally across product, marketing, BD, compliance, and member support
Responsibilities
- Monitor our International revenue baseline across the UK and CA, investigate anomalies, and provide early warning on revenue movement
- Support partner monitoring and escalations, including new offer setup, lookalike and recommender admin, partner click-report fixes, and partner ranking changes
- Run email campaign and performance monitoring, including anomaly investigation, re-targeting, send-failure triage, and churn-driver analysis
- Support experimentation and testing through experiment monitoring, reads, and promotion calls
- Handle member support and regulatory pulls, including DSAR and RTBF requests, complaint data, FCA regulatory returns, and marketplace-ranking monitoring, often against same-day or next-morning deadlines
- Represent analytics in forums and business reviews, translating technical detail for business partners
- Maintain our current suite of production models through scheduled refreshes, retraining, and redeploys
- Run data quality checks on model inputs and pipelines, and triage feed and pipeline issues
- Hand over models, pipelines, and reporting with monitoring and documentation to the permanent team at contract close
Technologies
- AI
- Support
- Marketing
- Python
- SQL
- Claude
- Code
We are an award-winning global SaaS company seeking an experienced, hands-on Senior Data Scientist for an International (UK and CA) run-the-business analytics and data science role. This is a 6-month contract with hybrid working and the potential to extend. You will work closely with product, marketing, engineering, business development, compliance, and member support, taking ownership of existing BAU processes end to end with minimal support while staying reliable under real deadlines. The role offers hybrid working, an award-winning work environment, a global organisation, and free breakfast.
Senior Data Scientist employer: EF Recruitment
EF Recruitment is an exceptional employer that values innovation and flexibility, making it an ideal place for a Hybrid Data Pipeline Engineer. With a strong focus on employee growth, the company offers opportunities to work with cutting-edge technologies in a collaborative environment, while the hybrid working model ensures a healthy work-life balance. Located in a vibrant area, employees benefit from a supportive culture that encourages professional development and meaningful contributions to international projects.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Scientist
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like EF Recruitment!
✨Show Off Your Projects
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 Senior Data Scientist at EF Recruitment.
✨Leverage Professional Networks
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 EF Recruitment.
✨Apply Directly through Our Website
When you find a suitable opening like Senior Data Scientist at EF Recruitment, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Senior Data Scientist
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 EF Recruitment, 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 EF Recruitment. 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 EF Recruitment
✨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 EF Recruitment!
✨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.
