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Job Opportunity: Senior Data Scientist
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Scientist based in United Kingdom.
This is an exciting opportunity to join a fast-growing, remote-first environment at the forefront of fraud prevention and financial risk intelligence. In this role, you will leverage advanced analytics, machine learning, and large-scale data to tackle complex fraud challenges with real-world impact. You will work closely with clients and cross-functional teams to design innovative risk solutions, optimize decision-making, and improve product performance. The position combines hands-on technical work with strategic problem-solving and stakeholder collaboration. Ideal for professionals who enjoy turning data into actionable insights, this role offers significant ownership, exposure to cutting-edge technologies, and the opportunity to influence the future of risk management on a global scale.
Accountabilities:
- Design, build, and deploy machine learning models to identify and prevent fraud across a variety of fintech and risk-related use cases.
- Drive a data-first culture by promoting analytical thinking and data-driven decision-making across internal teams and client engagements.
- Develop, monitor, and optimize performance metrics to measure the effectiveness of risk strategies and product outcomes.
- Conduct advanced analyses to uncover insights that improve fraud prevention, approval rates, and overall customer experience.
- Partner directly with clients to understand their fraud challenges and provide clear, actionable recommendations based on data insights.
- Build automated dashboards and self-service reporting solutions using business intelligence tools.
- Collaborate closely with engineering teams to productionize models, improve scalability, and enhance data infrastructure.
- Work cross-functionally with product, business, and engineering stakeholders to translate business requirements into impactful analytical solutions.
- Support the development of innovative risk mitigation strategies while balancing security, efficiency, and user experience.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Requirements:
- 7+ years of experience in data science, quantitative modeling, analytics, or related data-focused roles, ideally within fraud prevention, financial risk, or fintech environments.
- Strong hands-on expertise in Python and/or R, along with advanced SQL skills for large-scale data analysis.
- Experience with machine learning model development, deployment, and performance monitoring in production environments.
- Proficiency with BI and visualization tools such as Tableau, Sigma, Metabase, or similar platforms.
- Strong analytical skills, including experience with exploratory data analysis, cohort analysis, and extracting insights from complex datasets.
- Ability to communicate technical findings effectively to both technical and non-technical audiences, including external stakeholders and clients.
- Excellent critical thinking, problem-solving, and decision-making capabilities with a proactive and results-oriented mindset.
- Experience collaborating within cross-functional, globally distributed teams.
- Familiarity with big data technologies such as Spark is considered an advantage.
- Strong English communication skills, both written and verbal.
Benefits:


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- Competitive compensation package including cash compensation and equity participation.
- Remote-first working environment with the flexibility to work from anywhere.
- Flexible paid time off and additional year-end holiday breaks.
- Home office setup allowance to support your ideal remote workspace.
- Company-provided MacBook Pro and necessary equipment.
- Monthly meal allowance and social activity stipend.
- Annual health and wellness budget.
- Annual learning and professional development stipend.
- Opportunity to work alongside world-class professionals in a high-growth international environment.
- High levels of autonomy, ownership, and flexibility with a strong focus on results rather than hours worked.
- Inclusive and supportive culture that values work-life balance and personal well-being.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Why Apply Through Jobgether?
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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