Fraud Analytics and Data Science

Genpact

United States

On-site

USD 110,000 - 150,000

Full time

14 days+

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Job summary

A global professional services firm is seeking a Fraud Analytics & Data Science professional to develop machine learning models for fraud prevention. The ideal candidate will have extensive experience in data science and fraud risk management, and work collaboratively across various lines of business to implement data-driven strategies. This role offers competitive salary and the opportunity to work remotely within the USA, excluding specific locations.

Qualifications

5+ years of experience in fraud analytics, data science, or financial crime risk management.
Hands-on experience building and deploying ML models in a production fraud detection environment.
Strong command of Python, R, SQL, and data science libraries.

Responsibilities

Build and enhance fraud detection systems using statistical and machine learning techniques.
Monitor real-time and batch data to detect fraud trends and anomalies.
Design and maintain fraud rules and scoring logic for transaction monitoring systems.

Skills

Python

SQL

Data Science Libraries (pandas, scikit-learn, TensorFlow)

Education

Bachelor’s or Master’s in Data Science, Computer Science, Mathematics, Statistics, Engineering

Tools

Hadoop

Spark

Cloud Platforms (AWS, GCP, Azure)

Tableau

Power BI

Job description

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Genpact (NYSE: G) is a global professional services and solutions firm delivering outcomes that shape the future. Our 125,000+ people across 30+ countries are driven by our innate curiosity, entrepreneurial agility, and desire to create lasting value for clients. Powered by our purpose – the relentless pursuit of a world that works better for people – we serve and transform leading enterprises, including the Fortune Global 500, with our deep business and industry knowledge, digital operations services, and expertise in data, technology, and AI.

Inviting applications for the role of Fraud Analytics & Data Science

Genpact is looking for a seasoned professional to join as a Fraud Analytics & Data Science. This role is critical in driving data-driven fraud prevention strategies, developing advanced machine learning models, and delivering actionable insights to safeguard the bank’s products, platforms, and customers from evolving fraud threats.

Responsibilities

This role sits at the intersection of fraud risk management, data science, and business strategy, working across various lines of business including Retail Banking, Payments, Cards, and Digital Channels.

Build and enhance fraud detection systems using statistical and machine learning techniques.
Monitor real-time and batch data to proactively detect fraud trends, anomalies, and suspicious patterns.
Design and maintain fraud rules and scoring logic for transaction monitoring systems.
Advanced Analytics & Modeling:
Develop supervised and unsupervised machine learning models for fraud prediction (e.g., logistic regression, decision trees, random forests, XGBoost, neural networks).
Perform data wrangling, feature engineering, model training, validation, and performance monitoring.
Use anomaly detection, clustering, and network analysis to detect sophisticated fraud behaviors.
Work with data engineers and IT to ensure access to high-quality, real-time data feeds.
Design and build fraud-related data marts, dashboards, and alerting mechanisms.
Collaborate with fraud operations, compliance, IT, business units, and external partners.
Ensure alignment with regulatory expectations, model risk governance, and internal audit requirements.
Present insights and fraud risk updates to senior management and fraud committees.
Explore and implement new technologies (e.g., graph analytics, behavioral biometrics, NLP) for advanced fraud detection.
Stay current with fraud typologies, threat intelligence, and global fraud trends.

Qualifications we seek in you!

Minimum Qualifications

Bachelor’s or Master’s in Data Science, Computer Science, Mathematics, Statistics, Engineering, or a related field.
5+ years of experience in fraud analytics, data science, or financial crime risk management within banking or fintech.
Hands-on experience building and deploying ML models in a production fraud detection environment.
Strong command of Python, R, SQL, and data science libraries (pandas, scikit-learn, TensorFlow, etc.).

Preferred Qualifications/ Skills

Exposure to real-time fraud systems (e.g., SAS Fraud Management, Actimize, Falcon, etc.) is highly preferred.
Experience working with large datasets, Hadoop/Spark, and cloud platforms (AWS, GCP, Azure) is a plus.
Familiarity with tools like Tableau, Power BI, or similar for visualization and reporting.

The approximate annual base compensation range for this position is [$110,000 to $150,000]. The actual offer, reflecting the total compensation package plus benefits, will be determined by a number of factors which include but are not limited to the applicant’s experience, knowledge, skills, and abilities; geographic location; and internal equity

Work-from-Anywhere Roles – Anywhere in USA, preferably from East or West Coast in USA. “Los Angeles California-based candidates are not eligible for this role”

Location-based Roles (e.g., Richardson roles – metro area can be adjusted by role location) – “Los Angeles, California based candidates are not eligible for this role. area candidates are eligible for this role only.

Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. For more information, visit www.genpact.com . Follow us on Twitter, Facebook, LinkedIn, and YouTube.

Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a 'starter kit,' paying to apply, or purchasing equipment or training.

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