Data Scientist

Benefits

Parental leave

Not verified

Non-birth-parent leave

Not verified

Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

Not verified

Relocation assistance

Not verified

Childcare support

Not verified

Learning budget

Not verified

Verification

Not verified

Salary

Not verified

401(k) match

Not verified

Was this benefit information wrong? Tell us.

Schedule

Shift type

Not verified

Weekend work

Not verified

Application

Cover letter

Not verified

Assessment

Not verified

Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Data Scientist Herzliya AppsFlyer is a cutting-edge technology company that specializes in mobile attribution and marketing analytics. We run at a massive scale- t any given moment thousands of servers are consuming 150+ billion mobile app events, crunching our users' data, serving requests and communicating on a massive scale. Fueled by the AppsFlyer platform, Protect360 is the leading anti-fraud solution in the market, protecting advertisers from fraudulent traffic and saving millions of dollars for our customers. We detect fraudulent traffic (fake installs and attribution hijacking attempts) in real time using machine learning, deep learning, and advanced AI techniques applied on massive data streams. We're 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

Read the full description at careers.appsflyer.com. FewerJobs shows a source-linked preview and links to the original posting.