לוח משרות דרושים Data Scientist בהרצליה

We are looking for a talented and curious ML Data Scientist to join our growing Machine Learning team in Herzliya.

In this role, you will help create the full data lifecycle that underpins our models: from designing what data we collect, through curation and quality monitoring, to running rigorous experiments that drive model improvements. You will work closely with other ML and Data Engineering teams to ensure our models are trained on the best possible data, reaching the best accuracy, and that we deeply understand when and why they don't perform as expected.
Responsibilities
As an ML Data Scientist on this team, you will play a central role in shaping the data that powers our ML models. You will:
Investigate model failures - identify patterns, hypothesize root causes, and work with the team to implement fixes
Own data curation: evaluate, clean, and curate datasets to maximize model training quality
Design and execute experiments end-to-end: from defining the question and data collection escort, through analysis and statistical validation, to presenting clear conclusions and driving implementation
Define data collection strategies - collaborate with others to decide what data we should be collecting and why
Design and maintain monitoring solutions with others to ensure ongoing data quality and integrity at scale

Were looking for a data scientist to join our team and further improve fraud detection capabilities.
This position involves analyzing evolving fraud patterns, developing and deploying advanced prevention components, and leveraging domain expertise, data tools, and modern AI methods to stay ahead of emerging threats.
A partial list of our tech stack: Python (and its related scientific stack), Spark, TensorFlow/PyTorch, Kafka, AWS services, Airflow, Scala, BigQuery, and more
What you'll do:
Mine massive data sets to uncover fraud patterns and prevention opportunities.
Develop and productionize large-scale ML, DL, and AI models to detect and prevent fraudulent activity.
Translate business and product needs into scientific, explainable, and high-impact solutions.
Design and maintain end-to-end ML pipelines - from data ingestion and feature engineering to serving and monitoring in production.
Collaborate closely with product, engineering, and business teams to drive data-driven decisions.
Stay current with AI and ML research and evaluate new technologies to strengthen Protect360s algorithms.

We are looking for a Senior Product Manager to join our Analytics team within the Measurement group. In this role, you will own a core analytics domain used daily by global advertisers to measure, interpret, and optimize their marketing performance. You will work at the intersection of large-scale data, attribution complexity, privacy-driven measurement changes, and AI-powered capabilities - shaping how customers understand and rely on their marketing data.
This is a high-impact, highly visible role with direct influence on customer trust, product strategy, and the evolution of AppsFlyers analytics platform.
What youll do:
Own a core Analytics domain end-to-end - from discovery and strategy definition to execution, launch, and continuous improvement.
Define and drive the roadmap for dashboards, metrics, and data experiences serving enterprise marketing teams.
Balance stability, scalability, and innovation in a complex, data-intensive environment.
Lead initiatives that modernize and consolidate analytics capabilities across multiple attribution sources.
Shape the integration of AI-powered capabilities into analytics experiences, enhancing how customers interpret performance data.
Work closely with R&D (Backend, Frontend, Data Engineering) to build scalable, high-performance analytics products.
Partner with Sales and Customer Success to understand customer needs, support adoption, and strengthen trust in our measurement solutions.
Engage directly with customers to validate product direction and identify opportunities to improve clarity, usability, and performance insights.
Drive prioritization in a high-demand environment with multiple stakeholders and competing initiatives.