Explore complex datasets to identify fraud patterns and behavioral signals.
Build and evaluate machine learning models for fraud detection across account opening and identity risk.
Write clean, well-tested code and work with engineering to bring models into production.
Experian is a global data and technology company, powering opportunities for people and businesses around the world. We have an amazing team of 25,200 people in 32 countries, with a people-first, inclusive and purpose-driven culture.
Partner with the Business Unit Lead to identify gaps in decisioning performance and implement solutions.
Build production machine learning models to identify fraud in collaboration with other data scientists.
Communicate complex ideas to a variety of audiences, from Customer Success to Sales.
Signifyd helps merchants confidently grow their businesses by building trusted relationships with customers. Their advanced technology creates frictionless shopping experiences, and they are trusted by thousands of merchants across over 100 countries.
Prototype, evaluate, and deploy machine learning models for fraud detection with ongoing monitoring.
Design experiments to balance customer experience and fraud loss reduction.
Build anomaly detection systems to surface novel fraud vectors before scaling.
Moniepoint is Africa’s fastest-growing fintech, processing billions of Naira monthly with over 10 million accounts. They prioritize employee well-being and foster an inclusive culture.
Apply deep learning and foundation models to solve fraud detection and financial risk problems using large-scale behavioral and sequential datasets.
Take models through the complete ML lifecycle including data preparation, pretraining, deployment, and production optimization.
Collaborate with cross-functional teams and clients to translate model capabilities into actionable risk decisions.
The company is a fintech organization focused on fraud detection and financial risk using AI and deep learning. It operates with a remote-first culture and a collaborative, autonomous team.
Monitor transactions and customer accounts to identify and investigate suspicious or fraudulent activity.
Utilize fraud detection tools and SQL to analyze large datasets for patterns and anomalies.
Develop and implement fraud prevention strategies and stay updated on emerging threats.
Sezzle is a fintech company revolutionizing shopping with interest-free installment plans to financially empower the next generation. They are building an innovative, dynamic team passionate about creating a unique shopping journey.
Analyze fraud trends and risk signals to identify emerging threats and control gaps.
Design, tune, and evaluate fraud rules and detection strategies.
Partner with cross-functional teams to implement controls and improve outcomes.
Wave helps small businesses thrive so the heart of our communities beats stronger. They work in an environment buzzing with creative energy and inspiration, valuing diversity and inclusion.
Develop and optimize fraud prevention strategies using advanced analytics and machine learning.
Monitor fraud trends and client portfolios to identify emerging threats and recommend mitigation measures.
Serve as a fraud risk expert, providing analytical findings and recommendations to stakeholders.
The partner company specializes in fraud prevention and risk analytics for financial institutions, operating in a fast-paced payments environment. They are a remote-first organization with a focus on collaboration and work-life balance.
Analyze fraud risk trends across programs using enrollment, payment, and survey data.
Design and maintain fraud-risk indicators and collaborate with data engineering and product teams.
Translate findings into clear recommendations for stakeholders and support fraud investigations.
GiveDirectly delivers cash transfers directly to people living in poverty across 15 countries. The organization is one of Time100's Most Influential Companies of 2026, with a candid, analytical, and non-hierarchical culture.
Perform independent research using AI tools to identify novel emerging fraud trends.
Analyze large-scale messaging and voice traffic to detect fraudulent activity patterns.
Collaborate with data science and engineering teams to refine detection models and reduce false positives.
Twilio is shaping the future of communications, delivering innovative solutions to hundreds of thousands of businesses and empowering millions of developers worldwide. With a remote-first culture and a strong emphasis on connection and global inclusion, Twilio fosters a vibrant team of diverse experiences making a global impact each day.
Own the ML charter across identity resolution, fraud detection, risk scoring, and consumer intelligence, including strategy, roadmap, and delivery.
Build and grow a globally distributed team of ML engineers through hiring, coaching, and development.
Set the technical bar for model building, evaluation, deployment, and monitoring while holding the organization accountable.
Narvar is a platform that simplifies post-purchase experiences for retailers, driving customer loyalty through seamless interactions. With hubs in San Francisco, Atlanta, London, and Bangalore, the company serves over 125 million consumers and fosters a culture of low ego, high trust, and innovation.
Proactively hunt for advanced threats and dissect complex fraud vectors using hypothesis-driven threat hunting operations.
Apply and enrich the FT3 taxonomy to standardize threat intelligence across kill chain phases and API endpoints.
Collaborate cross-functionally to integrate threat intelligence, build agentic simulation workflows, and eliminate product vulnerabilities.
Stripe is a financial infrastructure platform for businesses, enabling millions of companies to accept payments and grow revenue. They are a large, global company with a mission to increase the GDP of the internet and a culture of innovation and collaboration.