דרושים » ניהול ביניים » Fraud Data Analytics Manager

Required Data Scientist
About the Role
The Data Science department plays a pivotal role in our company, generating value to us by developing algorithms and analytical production-grade solutions. We leverage advanced techniques and algorithms to provide maximum value from data in all shapes and sizes (such as classification models, NLP, anomaly detection, graph theory, deep learning, and more). As a Data Scientist, you will assume the classic data-science role of an end-to-end project development and implementation practitioner. Being part of the team requires a mix of hard quantitative and analytical skills, solid background in statistical modeling and machine learning, a technical data-savvy nature, along with a passion for problem-solving and a desire to drive data-driven decision-making.
What You'll Be Doing
Data Exploration and Preprocessing: Collect, clean, and transform large, complex data sets from various sources to ensure data quality and integrity for analysis
Statistical Analysis and Modeling: Apply statistical methods and mathematical models to identify patterns, trends, and relationships in data sets, and develop predictive models
Machine Learning: Develop and implement machine learning algorithms, such as classification, regression, clustering, and deep learning, to solve business problems and improve processes
Feature Engineering: Extract relevant features from structured and unstructured data sources, and design and engineer new features to enhance model performance
Model Development and Evaluation: Build, train, and optimize machine learning models using state-of-the-art techniques, and evaluate model performance using appropriate metrics
Data Visualization: Present complex analysis results in a clear and concise manner using data visualization techniques, and communicate insights to stakeholders effectively
Collaborative Problem-Solving: Collaborate with cross-functional teams, including product managers, data engineers, software developers, and business stakeholders to identify data-driven solutions and implement them in production environments
Research and Innovation: Stay up to date with the latest advancements in data science, machine learning, and related fields, and proactively explore new approaches to enhance the company's analytical capabilities.

We are looking for a Senior Product Manager to join our fast-growing AI & Data Science group. Reporting to our AI Product Director, you will be supporting the team building products for the next era of AI & Agentic Ecommerce - Where AI agents discover, negotiate, and purchase on behalf of users. You will lead the development of agent-ready experiences, ensuring interoperability with industry protocols, while driving measurable conversion, fraud, and cost outcomes for merchants. The ideal candidate will have a strong background in product management, a deep understanding of AI technologies, a passion for data driven insights, and the ability to translate complex technical concepts into market-leading products.
Responsibilities:
Define and execute the product roadmap for AI & Data Science solutions, aligning with company goals and market needs.
Drive the development and strategic vision for agentic commerce, agent-aware checkout and payment flows. Ensure protocol interoperability and compliance with leading industry standards such as AP2, Visa Trusted Agent Protocol, and Mastercard Agent Pay. Incorporate robust risk and trust signal mechanisms like agent verification, velocity controls, anomaly detection, and human-in-the-loop reviews, all while upholding Responsible AI guardrails.
Collaborate with cross-functional teams, including data science, engineering and commercial teams to bring products from conception to launch.
Conduct market research and competitive analysis to identify trends, opportunities, and challenges in the AI & Agentic Commerce space.
Work closely with data scientists and engineers to define product requirements, prioritize features, and ensure technical feasibility.
Develop and implement go-to-market strategies, ensuring products meet user needs and achieve commercial success.
Monitor product performance, gather feedback from users and stakeholders, and iterate quickly to enhance product offerings.
Stay abreast of advancements in AI & Agentic technologies to continually innovate and improve our product portfolio.

We are looking for a Data Scientist to join our team.
The ideal candidate is a highly motivated and self-driven individual with strong analytical and problem-solving skills. The Data Scientist will be responsible for analyzing data and developing models to help inform decisions and strategies for new products and business initiatives.
Responsibilities:
Work closely with stakeholders to understand business requirements and develop predictive models to detect fraud.
Develop and implement statistical models, machine learning and deep learning algorithms to solve complex problems in a production environment.
Perform exploratory data analysis and data visualization to gain insights and communicate findings.
Collaborate with cross-functional teams, including data engineers and software developers, to design and implement end-to-end solutions that can be deployed in production.
Implement advanced analytics tools and technologies to enhance reporting capabilities.

We are looking for a visionary and technically versatile Data Science Manager to join the Data Science & MLE group within our DS & Analytics organization.
In this pivotal role, you will lead a hybrid team of Data Scientists and Machine Learning Engineers, acting as the bridge between cutting-edge technical innovation and high-level business strategy. You won't just be managing a team; you will be the Technical Lead defining how we solve complex problems-from predicting player behavior to optimizing marketing budgets using the latest in Generative AI.
You will partner closely with Game Directors, Product Managers, and our central analytics teams to drive value across Zynga's diverse portfolio. If you are a leader who is "bilingual" in data-possessing deep Data Science expertise to guide methodology while bringing high MLE and Engineering skills to build scalable, production-ready systems-we want to hear from you.
Key Responsibilities:
Team Leadership & Mentorship: Recruit, retain, and develop top-tier talent within the Data Science & MLE team. Foster an inclusive culture of innovation where technical rigor meets creative problem-solving.

Technical Direction & Engineering Standards: Act as the hands-on Technical Lead for the domain. You will supervise the end-to-end development lifecycle-from research to production-enforcing high standards and MLOps to ensure our models are scalable and maintainable.
Strategic DS & Analytics Support: Drive the development of advanced analytical frameworks to solve core business challenges. You will guide the team in applying rigorous statistical and machine learning methods to areas such as Time Series Forecasting, Causal Inference, Marketing Optimization, Root Cause Analysis, and more.
Strategy & Collaboration: Partner with Game Directors, BI Platform PMs, and embedded analytics teams to define the data strategy and roadmap. You will ensure that our technical initiatives are directly aligned with company-wide goals and solving the right problems.
Global Alignment: Maintain a tight collaborative network with Data Science & Analytics managers in North America, ensuring global consistency in methodologies, knowledge sharing, and joint development.

We are looking for a Senior Data Products Manager to lead the strategy and evolution of our external data products, with a strong focus on customer needs and scalable, high-impact data solutions.
In this role, you will work directly with customers and internal stakeholders to understand how our data catalog is used across different use cases. Youll translate customer insights, usage patterns, and commercial input into a clear product vision and prioritized roadmap aligned with company objectives.
You will work closely with customer-facing data scientists and internal delivery teams to turn customer needs into production-ready data products. This includes collaborating with Partnerships to evaluate external data providers and defining requirements that guide the transformation of raw data into reliable, high-quality signals. You will also engage with the data pipeline itself, where different models are used to turn raw and unclassified data into coherent, scalable data products.
Responsibilities:
Own the strategy, vision, and roadmap for Exploriums external data products, guiding a delivery team of data developers and a team lead.
Lead customer discovery and translate insights into scalable product initiatives, requirements, and clear delivery plans.
Drive prioritization across competing needs, balancing customer value, business impact, feasibility, and time-to-market.
Lead the end-to-end data product lifecycle: discovery, definition, delivery, launch, adoption, and continuous improvement.
Collaborate cross-functionally with Data Science, Engineering, Sales, CS, and Partnerships to validate use cases and define measurable product success.
Write clear product specs and actionable tickets that guide the transformation of third-party data into production-grade data products.
Continuously improve existing products to expand coverage, improve accuracy, and unlock new customer use cases.
Define and track success metrics such as adoption, customer impact, accuracy, coverage, and performance.

This role combines strong Data Science expertise with the ability to independently lead impactful, production-grade work in complex environment.
The role focuses on developing AI capabilities on top of complex data in a security product environment. It requires independent thinking, analytical rigor, curiosity, flexibility, and strong technical ability. It also requires leading work end-to-end, breaking down complex problems, conducting structured research, and collaborating effectively across teams.
Key Responsibilities
Lead Data Science initiatives from problem definition through validation, production deployment, and monitoring
Develop AI-driven capabilities, including, domain-adapted models, prediction, anomaly detection, classification and AI agents
Adapt and fine-tune LLM-based solutions
Break down complex problems into clear components and drive structured research and iterative development
Choose the right approach for each problem, starting from simple baselines and progressing to more advanced methods when needed
Design solutions with awareness of production constraints and system limitations
Help shape solution architecture
Work closely with product, engineering, and other stakeholders across the company
Present findings, ideas, and results clearly at different levels, from technical peers to managers
Support team knowledge sharing, brainstorming, and guidance of other team members

We are seeking an experienced Product Manager - Decisioning (Risk Management) to own and evolve risk decisioning products. This role partners closely with ML Strategists, Engineering Leads and business stakeholders across our Card, BNPL, and emerging product products.

You will be responsible for defining and executing the product strategy that determines who we approve, on what terms, and at what expected loss, ensuring alignment with risk portfolio, regulatory requirements, and long-term unit economics. Transitioning from product-specific silos to a generic, high-velocity engine. This role requires strong judgment, deep analytical thinking, and the ability to translate complex risk logicinto scalable, explainable platforms.

Risk Strategy & Decisioning Ownership

Define and drive the product vision, strategy, and roadmap for Sunbits generic risk and credit decisioning systems. Translate business goals into clear, measurable product behavior across underwriting, pricing, limits, and lifecycle decisions, ensuring the platform can support diverse product lines without rebuilding core logic

Credit & Risk Decisioning Systems

Own the end-to-end decisioning platform (new product) , including real-time and lifecycle risk decisions, policy frameworks (rules and models), risk signal ingestion, persistence layers, and decisioning logic. Ensure the infrastructure is consistent, explainable, and scalable across multiple verticals.

Cross-Functional Partnership

Act as the glue in the "Decisioning Triangle," partnering with ML Leads and Engineer Leads to operationalize underwriting policies, while taking into account the trade-offs between approval rates, loss, revenue, and customer experience. Partner and balance competing requirements from various business owners (Heads of Card, BNPL, etc.) as well as Compliance, Legal, and Operations to ensure high-quality execution and regulatory integrity.

Hands-On Product Management

Act as a hands-on product manager for key initiatives, owning the full product lifecycle from discovery and definition through launch, iteration, and performance monitoring. Use data and experimentation to inform decisions and continuously improve outcomes. Identify and remove bottlenecks in the underwriting flow to drive toward high-automation and speed-to-market.

Risk Metrics & Business Outcomes

Own and drive core risk KPIs, including loss rate, performance, approval rates and customer friction introduced by risk controls. Ensure product decisions directly impact and improve business performance.

Lifecycle Risk Management

Treat risk as a continuous lifecycle by owning initial underwriting, line management, eligibility changes and early warning signals.

Are you passionate about harnessing cutting-edge data science techniques to protect the world from cyber threats? Do you thrive in the dynamic world of cybersecurity? If so, we invite you to join our innovative and forward-thinking team where you'll have the opportunity to shape the future of cybersecurity and impact millions of customers. As a Principal Data Scientist, you will apply your expertise in data analysis, machine learning, and cybersecurity to build new endpoint-based defense techniques against cyber-villains. You will be a driving force in designing and developing groundbreaking, ML-based security solutions that block attacks even before they begin.
Key Responsibilities
Contribute to a diverse and highly skilled research group that pioneers state-of-the-art technologies to protect our customers.
Utilize analytical rigor, statistical methods, programming, and data modeling to analyze vast amounts of data, applying your cybersecurity knowledge to guide our focus and approach.
Decompose complex problems scientifically and provide actionable insights and recommendations to both technical and non-technical stakeholders.
Lead and collaborate on end-to-end projects within the team and across engineering and product teams, from initial ideation to final deployment.

Required Data Scientist, Product Analytics
As a Data Scientist, you will shape the future of people-facing and business-facing products we build across our entire family of applications. By applying your technical skills, analytical mindset, and product intuition to one of the richest data sets in the world, you will help define the experiences we build for billions of people and hundreds of millions of businesses around the world. You will collaborate on a wide array of product and business problems with a wide-range of cross-functional partners across Product, Engineering, Research, Data Engineering, Marketing, Sales, Finance and others. You will use data and analysis to identify and solve product development's biggest challenges. You will influence product strategy and investment decisions with data, be focused on impact, and collaborate with other teams. By joining us, you will become part of a world-class analytics community dedicated to skill development and career growth in analytics and beyond. Product leadership: You will use data to shape product development, quantify new opportunities, identify upcoming challenges, and ensure the products we build bring value to people, businesses, and us. You will help your partner teams prioritize what to build, set goals, and understand their product's ecosystem. Analytics: You will guide teams using data and insights. You will focus on developing hypotheses and employ a varied toolkit of rigorous analytical approaches, different methodologies, frameworks, and technical approaches to test them. Communication and influence: You won't simply present data, but tell data-driven stories. You will convince and influence your partners using clear insights and recommendations. You will build credibility through structure and clarity, and be a trusted strategic partner.
Data Scientist, Product Analytics Responsibilities
Work with large and complex data sets to solve a wide array of challenging problems using different analytical and statistical approaches
Apply technical expertise with quantitative analysis, experimentation, data mining, and the presentation of data to develop strategies for our products that serve billions of people and hundreds of millions of businesses
Identify and measure success of product efforts through goal setting, forecasting, and monitoring of key product metrics to understand trends
Define, understand, and test opportunities and levers to improve the product, and drive roadmaps through your insights and recommendations
Partner with Product, Engineering, and cross-functional teams to inform, influence, support, and execute product strategy and investment decisions.

Required Data Scientist, Product Analytics
As a Data Scientist, you will shape the future of people-facing and business-facing products we build across our entire family of applications. By applying your technical skills, analytical mindset, and product intuition to one of the richest data sets in the world, you will help define the experiences we build for billions of people and hundreds of millions of businesses around the world. You will collaborate on a wide array of product and business problems with a wide-range of cross-functional partners across Product, Engineering, Research, Data Engineering, Marketing, Sales, Finance and others. You will use data and analysis to identify and solve product development's biggest challenges. You will influence product strategy and investment decisions with data, be focused on impact, and collaborate with other teams. By joining us, you will become part of a world-class analytics community dedicated to skill development and career growth in analytics and beyond.
Product leadership: You will use data to shape product development, quantify new opportunities, identify upcoming challenges, and ensure the products we build bring value to people, businesses, and us. You will help your partner teams prioritize what to build, set goals, and understand their product's ecosystem.
Analytics: You will guide teams using data and insights. You will focus on developing hypotheses and employ a varied toolkit of rigorous analytical approaches, different methodologies, frameworks, and technical approaches to test them.
Communication and influence: You won't simply present data, but tell data-driven stories. You will convince and influence your partners using clear insights and recommendations. You will build credibility through structure and clarity, and be a trusted strategic partner.
Data Scientist, Product Analytics Responsibilities
Work with large and complex data sets to solve a wide array of challenging problems using different analytical and statistical approaches
Identify and measure success of product efforts through goal setting, forecasting, and monitoring of key product metrics to understand trends
Partner with Product, Engineering, and cross-functional teams to inform, influence, support, and execute product strategy and investment decisions
Apply technical expertise with quantitative analysis, experimentation, data mining, and the presentation of data to develop strategies for our products that serve billions of people and hundreds of millions of businesses
Define, understand, and test opportunities and levers to improve the product, and drive roadmaps through your insights and recommendations.