Overview
On Site
USD 1-1
Full Time
Part Time
Accepts corp to corp applications
Contract - Independent
Contract - W2
Skills
Data Scientist
Fraud Analytics
Risk Analytics
Fraud Detection
Machine Learning
Predictive Modeling
Anomaly Detection
Behavioral Modeling
Network Analysis
Python
SQL
SAS
Tableau
Power BI
Data Visualization
Large Datasets
Data Cleaning
Data Wrangling
Data Analysis
Supervised Learning
Unsupervised Learning
AI Governance
Responsible AI
Cloud Platforms
AWS
Azure
GCP
Real-Time Fraud Detection
KPI Monitoring
Fraud Trends
Root Cause Analysis
Graph Analytics
Network-Based Fraud Detection
Compliance
Financial Crime
Regulatory Frameworks
Statistical Analysis
Data Science Strategy
Technical Communication
Business Intelligence
Deep-Dive Investigations
Model Deployment
Model Evaluation
Actionable Insights
Stakeholder Collaboration
Decision Support
Data-Driven Solutions
Data Engineering
Data Science Best Practices
Emerging Fraud Techniques
Cross-Functional Teams
Bachelors Degree
Masters Degree
Economics
Statistics
Computer Science
Cloud-Based Analytics
Advanced Analytics
Risk Modeling
Contract Data Scientist
Hybrid Analytics Role.
Job Details
Engagement Type
Contract
Short Description
In this role, you will analyze large and/or complex datasets, develop predictive models, and derive actionable insights that drive key business decisions.
Complete Description
We are seeking a highly analytical and detail-oriented Data Scientist with experience in Risk and Fraud analytics to join our growing team. This role will focus on developing and deploying machine learning models, statistical methods, and data-driven strategies to detect risky behaviors and prevent fraudulent activities across our products and services.
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.
Translatebusiness 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.
Required Qualifications
- Bachelor's or master's degree in data science, Computer Science, Statistics, Mathematics, Economics or a related field.
- 10+ years of professional experience in data science
- Proficient in Python, SQL, SAS and machine learning techniques
- Experience in responsible use of AI if used in solution design
Strong analytical skills and the ability to identify patterns and trends from data
- Experience working with large datasets and cloud platforms (e.g., AWS, Google Cloud Platform, Azure).
- Strong 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.
Required/Desired Skills
| Skill | Required/Desired | Amount | of Experience |
|---|---|---|---|
| Familiarity with graph analytics or network-based fraud detection tools. | Highly desired | 0 | |
| Knowledge of regulatory frameworks and compliance issues related to fraud and financial crime. | Highly desired | 0 | |
| Strong communication skills with the ability to explain technical solutions to non-technical stakeholders. | Highly desired | 0 | |
| Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, Economics or a related field. | Required | 0 | |
| Professional experience in data science. | Required | 10 | Years |
| Proficient in Python, SQL, SAS and machine learning techniques. | Required | 5 | Years |
| Experience working with large datasets and cloud platforms (e.g., AWS, Google Cloud Platform, Azure). | Required | 5 | Years |
| Understanding of supervised and unsupervised fraud detection techniques, including anomaly detection, behavioral modeling, and network analysis. | Required | 0 | |
| Experience with visualization tools like Tableau and Power BI. | Required | 5 | Years |
| Experience in responsible use of AI if used in solution design. | Required | 5 | Years |
| Strong analytical skills and the ability to identify patterns and trends from data. | Required | 0 |
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