Is the Senior Data Scientist, FinCrime role remote?

It's hybrid — ARQ expects some on-site time in London.

How much experience is required?

At least 5 years of relevant experience for this Senior Data Scientist, FinCrime role.

Where is the role based?

ARQ is hiring for this position in London.

What's the tech stack?

Joblaze extracted these technologies from the posting: Anomaly detection, Data Science, Fraud Detection, Machine Learning, Python, Risk Modeling.

What seniority level is this role?

ARQ targets senior candidates for this position.

Is this full-time or contract?

Full-time for this Senior Data Scientist, FinCrime role at ARQ.

Senior Data Scientist, FinCrime at ARQ

Joblaze summary

In the role of Senior Data Scientist at ARQ, the individual will focus on developing and deploying machine learning models to tackle financial crime and risk challenges, such as fraud detection and anomaly identification. Proficiency in Python and experience with large datasets are essential, along with a strong background in machine learning and data science. This position is ideal for someone with over five years of experience who thrives in fast-paced environments and enjoys collaborating across teams. ARQ's rapidly growing team is dedicated to innovating financial services for millions of customers.

Joblaze insights

Listed 9 days ago on Joblaze — tracked directly from ARQ's career page.
ARQ has 38 other open roles including Software Engineer (Java Backend), Senior Software Engineer (Java), Lead Software Engineer (Java).
6546 active Python roles on Joblaze right now.
797 active Machine Learning roles on Joblaze right now.
248 active Data Science roles on Joblaze right now.
Typical Python salary we track runs $125,000–$190,800 (median $160,000, across 3240 roles). See Python salary trends

Quick facts

Is the Senior Data Scientist, FinCrime role remote?: It's hybrid — ARQ expects some on-site time in London.
How much experience is required?: At least 5 years of relevant experience for this Senior Data Scientist, FinCrime role.
Where is the role based?: ARQ is hiring for this position in London.
What's the tech stack?: Joblaze extracted these technologies from the posting: Anomaly detection, Data Science, Fraud Detection, Machine Learning, Python, Risk Modeling.
What seniority level is this role?: ARQ targets senior candidates for this position.
Is this full-time or contract?: Full-time for this Senior Data Scientist, FinCrime role at ARQ.

From the original posting

What We're Looking For

We're looking for a Senior Data Scientist to help build the intelligence layer behind ARQ's financial products. You'll work on some of our most important risk and financial crime challenges, developing machine learning models that help us detect fraud, prevent losses, and make better decisions at scale.

This is a highly impactful role where you'll take problems from idea to production — partnering with Product, Engineering, and Operations teams to turn large-scale datasets into models that directly influence customer and business outcomes.

You'll join a fast-growing team helping build the future of financial services for more than 2 million customers across the Americas.

What You'll Be Doing

Design, build, and deploy machine learning models that solve real-world financial crime and risk challenges.
Work on problems such as fraud detection, chargeback prediction, anomaly detection, identity verification, and transaction monitoring.
Transform ambiguous business problems into measurable ML solutions.
Partner closely with Product and Operations teams to define requirements, success metrics, and decision frameworks.
Analyse large datasets to identify patterns, opportunities, and risks.
Build and maintain production-ready data pipelines and model-serving solutions.
Monitor model performance and continuously improve accuracy, reliability, and business impact.
Collaborate with Data Engineering and Backend Engineering teams to operationalise machine learning at scale.
Help shape the future of AI and machine learning capabilities across ARQ.

What You'll Need

5+ years of experience across Data Science, Machine Learning, Software Engineering, or related disciplines.
Strong Python skills and experience working with large-scale datasets.
Proven experience developing and deploying machine learning models in production environments.
Strong understanding of supervised learning techniques, particularly classification problems.
Experience with anomaly detection, fraud prevention, risk modeling, or related domains.
Ability to translate business challenges into data-driven solutions.
Experience working cross-functionally with Product, Engineering, and business stakeholders.
Strong communication skills and a pragmatic approach to problem-solving.
Comfortable operating in fast-moving environments with high ownership.

Nice To Have

Experience in financial crime, fraud prevention, AML, risk, or payments.
Experience in fintech, banking, or financial services.
Backend engineering experience and familiarity with production systems.
Experience building real-time decisioning or risk platforms.
Familiarity with modern MLOps practices and model monitoring.

Benefits

Competitive salary and benefits
Stock options, so you own part of what you build
Discretionary performance bonus
The latest tools and technology
A world-class team that will challenge and grow your skills
The opportunity to help build the best fintech app in Latin America
Office Policy: 3-4 days a week in-office