דרושים » תוכנה » Fraud Data Analyst

As we scale and evolve our fully automated fraud prevention strategies, we are seeking a Data Analyst to join our growing Fraud Analytics team.
We operate in a data-rich, fast-paced environment, processing billions of data points annually, and play a critical role in safeguarding large enterprises from fraud. In this role, you will work at the intersection of data analysis, fraud strategy, and automation, collaborating closely with engineering, data science, and commercial teams to develop scalable fraud detection solutions.
This is a high-impact role with significant ownership and cross-functional collaboration in a team with tremendous room for growth. If you are highly motivated, data-driven, and thrive in a fast-moving environment - you belong with us.
Key Responsibilities:
Develop and refine fraud detection strategies by analyzing complex datasets and identifying fraud patterns.
Partner with cross-functional teams, including software engineers, data scientists, and commercial stakeholders, to develop scalable fraud solutions.
Conduct deep-dive risk analyses, leveraging multiple data sources to assess fraud threats and define innovative solutions.
Monitor and automate fraud detection processes to enhance efficiency and effectiveness.

we are looking for a Junior Fraud Data Scientist.
As a Junior Fraud Data Scientist, you will contribute to our ongoing efforts to protect our ecosystem from financial threats and abuse. Working under the guidance of senior team members in a data-rich environment, you will assist in identifying malicious behaviors, support detection coverage, and help maintain our automated mitigation strategies.
This role is designed for an analytical professional with 1-2 years of experience who wants to build a deep expertise in adversarial data, learn from an experienced team, and develop their technical skills across modern cloud data platforms.
What You Will Be Doing
Exploratory Data Analysis: Support the team by mining behavioral and transactional datasets to help identify anomalies and emerging fraud patterns.
Model Support & Optimization: Assist in building, tuning, and validating machine learning models (e.g., XGBoost, LightGBM) under the supervision of senior data scientists.
Feature Generation: Extract, engineer, and prepare new data features from structured and unstructured sources to help improve model performance.
Dashboarding & Monitoring: Build and maintain internal dashboards and pipelines to track model health, data drift, and key fraud KPIs.
Cross-functional Collaboration: Work alongside Fraud Analytics and Product teams to help translate operational fraud insights into automated data solutions.

We are expanding our Fraud Intelligence Unit and need passionate, sales-focused, fraud fighters to join our team.

Reporting to the Global Fraud Intelligence Director, you will be responsible for conducting deep-dive, targeted analysis of fraud patterns to support high-impact, engagement strategies for prospective customers, with the goal of supporting the sales team and business in securing revenue growth. Unlike broader trend analysis roles within the team, this position focuses on generating highly tailored insights for a defined set of priority prospects, helping articulate the need for our advanced fraud and financial crime prevention solutions.

You will work closely with internal stakeholders to analyse us and external data with a hypothesis-driven approach, uncovering specific vulnerabilities, attack patterns, and risk exposures relevant to individual organisations or segments. Your work will translate complex data into compelling, evidence-based narratives that highlight both the impact of fraud and the urgency of addressing it.

Key responsibilities:
Support the Sales team in the generation and progression of revenue-generating opportunities.
Conduct deep, targeted analysis of our data to identify customer- or segment-specific fraud patterns, risks, and vulnerabilities.
Apply advanced analytical techniques and hypothesis-driven investigation to uncover insights that are not visible through high-level trend analysis.
Leverage AI-assisted analytical tools to enhance the scale and speed of analysis, while applying rigorous data validation and expert judgment to ensure accuracy and relevance.
Translate analytical findings into tailored, prospect-relevant narratives that clearly articulate fraud exposure, business impact, and the value of mitigation strategies.
Develop insight-driven materials that support commercial engagement, including customer-specific briefings, strategic reports, and pre-sales narratives.
Collaborate closely with sales, marketing, and regional teams to align analytical tasks with customer priorities and commercial objectives.
Design and develop effective data visualisations that simplify complex findings and strengthen the impact of customer-facing storytelling.
Present findings internally as well as directly to customers, demonstrating credibility through data-backed insights and clear articulation of fraud risks.
Build and maintain analytical frameworks, datasets, and repeatable methodologies that support scalable customer-focused analysis.
Identify opportunities to enhance analytical workflows through automation and AI, while ensuring critical thinking and professional judgment guide all conclusions.
Stay current with emerging fraud trends, analytical techniques, and AI capabilities, applying them to continuously improve the precision and impact of insights.

we are looking for a Fraud Data Scientist.
As a Fraud Data Scientist, you will be at the front lines of protecting our ecosystem from sophisticated financial fraud and abuse. You will join a high-impact team operating in a data-rich, high-frequency environment where seconds matter.
In this role, you will take ownership of the end-to-end machine learning lifecycle-from uncovering complex fraud patterns to deploying highly scalable, real-time models into production. You will collaborate closely with Engineering, Product, and Risk Operations to build robust defenses that balance strict security with a seamless user experience.
What You Will Be Doing
Model Development & Deployment: Design, train, and deploy advanced machine learning models (e.g., gradient boosting, anomaly detection, graph networks) to detect and mitigate fraud in real-time.
Production Ownership: Take full ownership of putting models into production systems, ensuring low-latency execution and high reliability.
Agentic Workflows: Research, build, and implement Agentic flows and LLM-driven orchestration to automate multi-step fraud decisioning, logic routing, and investigation paths.
Adversarial Analysis: Conduct deep-dive exploratory analysis on massive datasets to identify emerging fraud vectors, loops, and coordinated attacks.
Feature Engineering: Build and optimize real-time streaming and batch features to improve model signal and precision.
Experimentation & Monitoring: Design rigorous shadow-testing and A/B testing frameworks for new models. Set up continuous monitoring pipelines to catch data drift and performance degradation early.

Required Cyber Data Analyst
Description
We are redefining trust in blockchain through advanced, integrated security. Our on-chain security platform is trusted by leading Web3 companies-including Coinbase, MetaMask, Uniswap, Backpack, Stellar, and others-to detect, understand, and automatically prevent or minimize the impact of fraud, scams, hacks, and financial threats.
We are backed by top-tier global investors including Sequoia Capital, Ribbit Capital, and Cyberstarts-firms known for supporting the most innovative and influential companies in technology and cybersecurity.
As a Senior Data Analyst within our R&D team, you will shape how we understand data, uncover trends, and drive strategic decisions across. Working closely with cross-functional teams, you will turn complex datasets into actionable insights that directly influence our business growth and product direction.
Your Chain of Impact:
Identify, analyze, and interpret trends or patterns in complex datasets to uncover actionable insights.
Analyze large datasets to provide clear, impactful recommendations that support operational and strategic goals.
Develop scalable data processes and infrastructure to support internal stakeholders.
Build and maintain dashboards, reports, and KPIs to monitor and improve company performance.
Translate business questions into analytical models and craft compelling data visualizations that tell the story.
Partner with cross-functional teams to understand business needs and design data-driven solutions.

We are looking for a hands on, proactive, and impact driven Senior Business Analyst to join our data team. In this role, youll shape how the company measures success and help embed a strong data driven culture across every domain, from business operations to product, finance, and beyond.

This is an opportunity for someone who thrives in dynamic, fast changing environments, loves building from scratch, and is just as comfortable running deep analyses and leading cross functional measurement discussions as they are partnering with data engineering to design scalable data models that empower the entire organization.

In this role you will
Collaborate with cross functional teams to understand business objectives and develop data driven solutions
Lead measurement and metric discussions with diverse stakeholders, translating needs into clear, consistent, and actionable definitions
Conduct deep dive analyses to uncover insights and deliver impactful recommendations
Partner with data engineering to design scalable data models and improve data accessibility
Build clear, intuitive dashboards and reports to track performance and enable self serve analytics
Proactively monitor business metrics and provide timely insights to optimize operations and identify opportunities
Promote a data driven culture by empowering teams to use data confidently in decision making
Mentor teammates and contribute to the growth and maturity of the data function

As our company continues to scale, were looking for a Product Data Analyst to join our Product team. In this role, youll blend strong analytical skills with operational execution to help our product and go-to-market teams make data-informed decisions. About 70% of your time will be spent analyzing product and customer data, building dashboards, and delivering insights that will shape the future of our product. The remaining 30% will focus on supporting our data operations - ensuring our data processes, tools, and reporting cadences run efficiently, implementing best practices.

Youll sit directly within the Product organization, collaborating closely with Product Managers, Designers, and Engineers to improve how we use data across a growing suite of B2B SaaS products and within our organization.

Responsibilities
Analytics
Analyze product usage and customer behavior across multiple SaaS products to uncover insights that guide roadmap priorities and growth opportunities.
Build and maintain dashboards and reports in Snowflake, Redash, Metabase, and Mixpanel using SQL to support Product, GTM, and leadership teams.
Define and track key metrics such as activation, retention, adoption, ARR growth, and engagement.
Run ad-hoc analyses to answer business questions and support experiments or feature evaluations.

Data Operations
Collaborate with Engineering and Data teams to enhance analytics setup and data workflows.
Partner with Engineering teams to ensure clean data instrumentation, event tracking, best practices for data, and measurement implementation across product features.
Maintain and improve data quality processes, pipeline documentation, and operational standards to support reliable decision-making.

We are looking for a Senior Detection Researcher to join us and play a key role in designing the next generation of our detection and enforcement systems.
What You'll Do:
Lead research initiatives to design, implement, and deploy innovative detection methods at scale, from early-stage discovery to production rollout.
Investigate adversarial attack patterns, dissect how threat actors operate, and develop countermeasures that are resilient to adaptation and evasion.
Engineer and curate features across large-scale data pipelines (Reputation signals, behavioral signals, network-level attributes) to fuel detection models and algorithms and reputation systems.
Collaborate closely with engineering, product, security research, data science, and incident response teams to translate research findings into production-grade enforcement rules and models.
Leverage AI tools daily to maximize output and drive high-quality results
Own end-to-end customer-facing research for strategic accounts. conduct deep-dive traffic analysis, resolve complex escalations, and drive detection improvements based on real-world adversarial activity.
Contribute to the team's detection quality practices by reviewing colleagues' work, monitoring production anomalies, and iterating on precision/recall trade-offs.

Were looking for a sharp and driven Data Analyst to join our fast - paced Data Labs team. As part of a high-performing group of analysts, youll handle complex, custom requests from some of the biggest names in the market, turning raw data into strategic, ad hoc insights. The work is intense and constantly evolving - it requires strong analytical skills and the ability to work independently under pressure. Youll need to be curious, adaptable, and willing to dive deep to find answers where others might stop. If you thrive in a demanding environment and are excited by the opportunity to make a real impact, we want you on our team.
What does the day to day of a Big Data Analyst Customer Facing (Data Labs) look like:
Building custom-made reports end to end - from meeting with the client and understanding their needs, to writing the code and setting up the report for ongoing delivery.
Apply your expertise in quantitative analysis and data mining to turn data into insights.
Conduct research and develop tools which will help answer client's business. questions by using our raw data sets and algorithms.
Partner with Engineering teams to establish an infrastructure to scale solutions.
Partner with Advisory Services team of Consultants to answer strategic business questions and deliver custom data products seamlessly.

We are looking for a native French speaker with a high level of proficiency in English to join our Annotation and Analysis team at the as a Data Annotator and Analyst. In this role, you will work with large volumes of data in both French and English, annotating and analyzing datasets used to evaluate and train machine learning models, including large language models (LLMs). Your work will involve reviewing model outputs and preparing high-quality training data that supports the development and continuous improvement of AI-driven products. In addition, as part of the job, you will conduct complex analysis on the annotated data and provide insights to the other stakeholders. This position is ideal for someone passionate about linguistics and data, and who enjoys working on detail-oriented tasks that directly impact model quality. As part of a collaborative, cross-functional team, you will work closely with Data Scientists and Product Managers to ensure that datasets are accurately labeled and annotation standards support the development of reliable machine learning systems.
Responsibilities :
Evaluate the quality of machine-translated text, with a focus on French language accuracy and fluency.
Annotate and assess AI model responses to support systematic evaluation and improvement of model performance.
Create high-quality annotated datasets used to train and evaluate LLMs and other NLP models.
Write and refine LLM prompts that support scalable human annotation workflows.
Collaborate with cross-functional teams, including Data Scientists and Product Managers, to communicate linguistic nuances and implications of French translations on model behavior and user experience.
Analyze annotated data and evaluation results to identify patterns, assess model quality, and surface insights for model improvement.