Data Scientist

  • Atlanta, GA
  • Posted 12 hours ago | Updated 12 hours ago

Overview

On Site
$60
Contract - W2

Skills

Data Scientist
Python
SQL
SAS
machinelearning
AWS OR GCP OR AZURE

Job Details

Role : Data Scientist
Location : Atlanta, GA
Duration : Contract
Contract Type: W2

Looking for only locals.

Required Education:
Bachelor s degree in data science, Computer Science, Statistics, Mathematics, Economics or a related field
Preferred Education:
Master s degree in data science, Computer Science, Statistics, Mathematics, Economics or a related field
Required Experience, Knowledge, and Skills:
Familiarity with graph analytics or network-based fraud detection tools
Knowledge of regulatory frameworks and compliance issues related to fraud and financial crime
Strong communication skills with the ability to explain technical solutions to non-technical stakeholders
Professional experience in data science (10 Years)
Proficient in Python, SQL, SAS, and machine learning techniques (5 Years)
Experience working with large datasets and cloud platforms (e.g., AWS, Google Cloud Platform, Azure) (5 Years)
Understanding of supervised and unsupervised fraud detection techniques, including anomaly detection, behavioral modeling, and network analysis
Experience with visualization tools like Tableau and Power BI (5 Years)
Experience in responsible use of AI if used in solution design (5 Years)
Strong analytical skills and the ability to identify patterns and trends from data
Key Responsibilities:
Collect, clean, and analyze large, complex datasets from multiple sources
Develop predictive models and machine learning algorithms to support decision-making and improve business performance
Translate business problems into data-driven solutions with measurable impact
Develop and deploy machine learning models to detect, predict, and prevent fraudulent transactions and behavior patterns
Analyze large volumes of structured and unstructured data from multiple sources to identify fraud trends and root causes
Collaborate with fraud operations, engineering, and compliance teams to implement real-time fraud detection solutions
Design and monitor KPIs to evaluate model performance and improve fraud detection systems over time
Conduct deep-dive investigations into fraud cases, creating detailed reports and actionable insights
Stay current with emerging fraud techniques, industry best practices, and data science tools

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