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Expert Data Scientist, Fraud Risk Detection

  • $103.7k–179.7k/yr
  • Posted 3 days ago · via SmartRecruiters

Hiring in some regions only

Develop fraud detection models using Python and PySpark for financial institutions

Investigate large datasets to identify fraud patterns and develop machine learning models for fraud detection across account opening, account takeover, and identity risk. Evaluate models using metrics like ROC/AUC, precision/recall, and fraud capture rate. Develop and validate predictive features using identity, transactional, and behavioral data. Write clean, efficient Python and PySpark code to deploy models into batch, retro, or real-time d...

Why This Role?

Work with senior data scientists and engineers from problem definition through deployment

Key Responsibilities

  • Investigate large datasets to identify fraud patterns and attack methods
  • Develop machine learning models for fraud detection across account opening, account takeover, and identity risk
  • Evaluate models using ROC/AUC, precision/recall, fraud capture rate, and false-positive rate
  • Develop and validate predictive features using identity, transactional, and behavioral data
  • Write clean, efficient, well-tested Python and PySpark code for model deployment
  • Monitor feature quality, model performance, and fraud-pattern drift

Requirements

  • Eagerness to collaborate and empathy
  • Ability to investigate surprising signals in data and translate insights into deployed models
  • Experience with exploratory analysis and fraud label development
  • Skills in translating ambiguous fraud problems into hypotheses and analytical plans
  • Proficiency in Python and PySpark for writing clean, efficient, well-tested code
  • Knowledge of model evaluation metrics like ROC/AUC, precision/recall, and Gini

Required Skills

machine learningpythonpysparkdata analysisfraud detectioncollaborationempathydata investigationfeature engineeringPython programming

Indonesia Context

Working Hours Overlap:
Flexible — work your own hours
See remote (USD) vs local pay →
View Original Description from SmartRecruitersShow more

Original description from SmartRecruiters

Overview Experian's Fraud Analytics & Commercialization operates across four main functions. These include client engagement analytics, scalable and custom analytics for financial institutions, fraud analytics consulting, and solution integrity and enablement for production-ready platforms. We're looking for a motivated Data Scientist to help build fraud detection models and features that identify high-risk activity while minimizing friction for legitimate customers. Core skills for this role include an eagerness to collaborate, and empathy. You will will dig into surprising signals in the data and to learn how that insight becomes a deployed model. You will help investigate the latest fraud patterns, build features, and train and evaluate machine learning models. You will work with senior data scientists and engineers starting with problem definition through feature engineering, experimentation, and deployment. You will be a developing programmer, ready to translate theoretical principles into production-ready solutions. We continue to sharpen through research and the engineering that turns those findings into tools and systems built for commercialization. This is a remote role and you will report into the Sr. Manager of Fraud Analytics. What you'll do Investigate large datasets, including exploratory analysis and fraud label development, to identify latest fraud patterns, attack methods, and behavioral signals. Translate ambiguous fraud and risk problems into clear hypotheses, analytical plans, model requirements, and measurable success criteria. Develop machine learning models for fraud detection across account opening, account takeover, and identity risk. Evaluate models using metrics like ROC/AUC/KS/Gini, precision/recall, fraud capture rate, false-positive rate, customer friction, and fraud losses prevented. Develop and validate predictive features using identity, transactional, consumer credit history, device, behavioral, temporal, velocity, network, and third-party data. Write clean, efficient, well-tested Python and PySpark code, and collaborate with teams to bring models and features into batch, retro, or real-time decisioning environments. Monitor feature quality, model performance, population changes, and fraud-pattern drift Design and present analyses for model behavior, tradeoffs, risks, and recommendations Follow appropriate standards for data privacy, model documentation, explainability, validation, and governance. Qualifications At least 3 years of experience in data science, machine learning, statistical modeling, or a related quantitative field Bachelor's or advanced degree in computer science, statistics, engineering, data science, or another quantitative discipline Direct experience developing fraud-detection, identity-risk, credit-risk, financial-crime, or other adversarial risk models. Demonstrated experience creating meaningful fraud features Proficiency in Python and PySpark, with experience writing modular and tested code for large datasets and distributed or cloud data systems. Experience using common data science and machine-learning tools such as pandas, NumPy, scikit-learn, XGBoost, TensorFlow, or comparable technologies. Knowledge of supervised learning, model evaluation, feature selection, statistical inference, experimentation, and model calibration. Experience navigating challenges common to fraud modeling, including class imbalance, delayed or incomplete labels, changing attack patterns, and model drift. Experience moving models beyond experimentation and into production, either directly or in close partnership with engineering teams. #LI-Remote Benefits/Perks: Great compensation package and bonus plan Core benefits including medical, dental, vision, and matching 401K Flexible work environment, ability to work remote, hybrid or in-office Flexible time off including volunteer time off, vacation, sick and 12-paid holidays Explore all our exciting benefits here: https://yourexperianbenefits.com/cand-index.html Our uniqueness is that we celebrate yours. Experian's people first, inclusive and purpose-driven culture is multi award-winning. We have won World's Best Workplaces™ 2025 (Fortune Global Top 25), and Great Place To Work™ in 26 countries to name a few. Experian's recruitment process is conducted only through authorised channels. Recruitment communications will only be sent from an @ experian.com email address. Experian will never ask candidates to make any payment as part of a recruitment process. Our compensation reflects the cost of labor across several U.S. geographic markets. Within this range, individual pay is determined by work location and additional factors such as job-related skills, experience, and education. You will be eligible for a variable pay opportunity and a comprehensive benefits package. Experian is proud to be an Equal Opportunity Employer for all groups protected under applicable federal, state and local law, including protected veterans and individuals with disabilities. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity.

Salary Context

Similar Data & Analytics roles on LokerDollar pay around $115k/yr (range $9.7k–1000k/yr, n=187 active listings).

Hiring at Experian

Experian has 67 other active roles on LokerDollar and has been hiring here since Mar 27, 2026 — across Data & Analytics, AI, Sales & Business Development.

View all Experian openings →

Market context

  • VERIFIEDStated pay is 23% above the role median of $115,000/year (n=187 pay-disclosing listings).
  • VERIFIEDExperian: 140 postings in the last 3 months, 302 all-time on LokerDollar.
  • VERIFIEDCompany first seen Mar 27, 2026.
  • VERIFIEDThis listing first seen Oct 13, 2026.
  • VERIFIEDLast verified live Oct 13, 2026.

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Company
Experian
Salary
$103.7k–179.7k/yr
Job Type
full time
Location
Remote · Some regions only
Seniority
senior
PostedNewNew & verified
Oct 12, 2026

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Frequently asked questions

Is Expert Data Scientist, Fraud Risk Detection at Experian a remote job?
Yes, Expert Data Scientist, Fraud Risk Detection at Experian is remote, but the employer hires only in certain regions. Check the listing for location requirements before applying.
What is the salary for Expert Data Scientist, Fraud Risk Detection at Experian?
The listed pay range for this role is $103.7k–179.7k/yr.
What type of employment is Expert Data Scientist, Fraud Risk Detection at Experian?
This is a full time position.
How do I apply?
Click the "Apply" button on this page to go to the official application at Experian.

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