Overview
On Site
Depends on Experience
Full Time
Skills
Data Science
risk management
machine learning
Pyspark
AI/ML
AWS
Job Details
Role: Data Scientist
Location: Alpharetta, GA
Mode Of Hire: Full Time
Experience: 09+ years
Skills Required:
- Experience in fraud analytics, risk management or financial crime analytics in the banking sector with an additional emphasis on transaction monitoring
- Machine Learning and Business Articulation
- Expertise: Extensive experience in designing, developing, and deploying machine learning models to detect and mitigate fraud. Candidate should demonstrate a high degree of capability to translate client business statements/briefs into data-driven solutions.
- Fintech & Fraud Detection: Background in the Fintech industry, with specific experience in financial crime and fraud detection, applying data science to solve real-world business problems.
- Advanced Tools and Platforms: Experience with tools such as PySpark, Databricks, AWS, or Google Cloud Platform for processing large datasets, training models, and deploying them at scale.
- Candidate must demonstrate following in their experience
- SME level expertise on Fraud Patterns and associated solutions
- Thorough knowledge of AWS ecosystem in context of AI/ML solutions
- Understanding Model Risk Management requirements as part of solution
- Excellent command of PowerPoint for creating apt business presentations
- Expertise in AI / ML with strong focus on leveraging cloud platforms like AWS to build scalable, production-grade applications.
- Strong experience with advanced SQL and good to have experience in Pyspark.
- Good understanding or experience of working in AWS
- Excellent written and verbal communication skills.
- Strong understanding of fraud patterns and digital transaction behaviors.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.