Senior Fraud Data Scientist - Remote & Equity

Remotedxb; Dubai; On-site; AED 240,000 - 360,000; Full time

Benefits offered by this job

Remote-first culture

401k

Unlimited PTO

Health, dental, and vision insurance (

US)

Job summary

Remotedxb in Dubai is seeking a data scientist to build advanced fraud detection models using ML and statistics. You will collaborate with engineering, product and operations to design scalable fraud systems and analyze large datasets to spot patterns and anomalies.

Ideal candidates have 3+ years in data science or ML with a focus on fraud prevention, strong Python skills, and experience with Spark or Dask in distributed environments.

Qualifications

• 3+ years of experience in data science, ML, or related field
• Focus on fraud prevention and/or anti-money laundering
• Proficiency in Python
• Experience with large datasets using distributed systems like Spark and Dask
• Strong knowledge of ML algorithms and statistical techniques
• Excellent analytical and problem-solving skills
• Ability to work independently and collaboratively in a fast-paced startup environment

Responsibilities

• Develop and implement advanced fraud detection models using ML and statistical techniques
• Collaborate with cross-term teams including engineering, product, and operations to design fraud detection systems
• Analyze large volumes of data to identify patterns and anomalies indicative of fraudulent behavior
• Evaluate and optimize existing fraud detection models to adapt to changing trends
• Communicate complex data analysis and model performance results to stakeholders
• Ensure data privacy and security compliance in all aspects of fraud detection

Skills

Analytical thinking

Data storytelling

Teamwork

Fraud prevention

Statistical methods

Tools

Python

Apache Spark

Dask

Job description

Remotedxb in Dubai is seeking a data scientist to build advanced fraud detection models using ML and statistics. You will collaborate with engineering, product and operations to design scalable fraud systems and analyze large datasets to spot patterns and anomalies.

Ideal candidates have 3+ years in data science or ML with a focus on fraud prevention, strong Python skills, and experience with Spark or Dask in distributed environments.