Equifax is where you can power your possible. If you want to achieve your true potential, chart new paths, develop new skills, collaborate with bright minds,  and make a meaningful impact, we want to hear from you.

Do you enjoy solving problems, looking at problems through a different lens, and working closely with customers to develop new innovative solutions? Are you interested in utilizing your skills in machine learning to catch fraudsters?

Equifax is looking for a Data Science Lead / Principal Data Scientist to join our Equifax Digital Solutions (EDS) team. This opportunity will need to be based out of our Boise, ID office and will follow our hybrid work schedule (Tuesday - Thursday in office).

What is Equifax Digital Solutions? 

Equifax Digital Solutions (EDS) has developed a powerful suite of solutions designed to help global businesses navigate the complexities of identity resolution and fraud prevention in the digital age. EDS currently provides digital identity and fraud prevention solutions to thousands of global merchants, financial institutions,  and payment providers.  At its core, the EDS Data & Analytics team leverages Equifax's vast data assets and advanced machine learning to provide solutions for verifying and authenticating identities, assessing risk, and protecting consumers against fraudulent transactions.

In EDS, we're committed to collaborative innovation, working hand-in-hand with our customers to develop solutions that tackle their most pressing identity resolution and fraud prevention challenges.

What you’ll do

We're seeking a Data Science Lead / Principal Data Scientist, with a proven track record in machine learning and AI,  to lead our payments and transaction protection solutions. The ideal candidates will possess experience in the financial services industry and/or consulting and have a passion for applying machine learning to real-time business problems. As a key member of our team, you'll collaborate closely with our engineering teams and strategic customers to develop cutting-edge payment and transaction monitoring solutions.  

Subject matter expertise 

Lead data-science machine learning and AI projects focused on real-time payments fraud preventionLeverage your experience in machine learning and AI to drive data-science solutions for customers Collaborate with business partners, customers and stakeholders to define solution approach Serve as our data science thought leader in payments and transaction fraud prevention

Hands on Data Science 

Apply ML/AI frameworks and best practices for model buildingDeep mathematical understanding of statistics and machine learning Incorporate best practices for machine learning(ML) and artificial intelligence (AI) buildingReview, support and provide best practices for analysis of machine learning(ML) and artificial intelligence (AI) modelsEvaluate ML model performance, explainability, and  selected modeling techniques are appropriate and align with desired project outcomes

Partner with the Business

Lead ML/AI and data-science partnerships and engagements with customersIdentify opportunities to improve existing models and exploit our intellectual propertyPartner with diverse Equifax teams to identify and explore opportunities for the novel application of machine learning (ML) and artificial intelligence (AI)Provide insights and solutions by understanding the business, product, data, and customer perspectiveDevelops new techniques/methodologies for building solutions for a specific business challenges based on available data

What experience you need 

Masters Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, Engineering or related field AND 5+ years of hands on data-science experience (e.g., training and evaluating machine learning models, applying statistical techniques, and reporting results)Proven track record of designing and developing predictive models in real-world applications with a thorough understanding of diverse machine learning algorithms, including:Supervised Learning: Regression (linear, polynomial, logistic, etc.), classification  random forest, XGBoost, LightGBM, Catboost, SVMs, etc.), and ensemble methods (boosting, bagging, stacking)Unsupervised Learning: Clustering (k-means, hierarchical, DBSCAN), dimensionality reduction (PCA, t-SNE), and anomaly detection techniques (RRCF, IsoForest, AutoEncoders)Deep Learning: Neural networks (feedforward, convolutional, recurrent), autoencoders, and transformer modelsExperience with model performance evaluation, model interpretability, prediction explanations and strategy optimizationExpertise with Python and SQL for data manipulation, analysis, and ML model developmentExperience with cloud computing (AWS or GCP) Knowledge of ML operations for managing the entire lifecycle of ML models, including deployment, monitoring, and retraining

What could set you apart

Experience with Natural Language Processing (NLP) for feature extractionExperience with Computer Vision (CV) for Identity VerificationExperience with Generative AI Experience with First / Third Party Fraud Prevention or Identity Resolution Experience with real-time systems Experience with Graph Networks

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We offer comprehensive compensation and healthcare packages, 401k matching, paid time off, and organizational growth potential through our online learning platform with guided career tracks.

Are you ready to power your possible?  Apply today, and get started on a path toward an exciting new career at Equifax, where you can make a difference!

Primary Location:

USA-ID-Boise

Function:

Function - Data and Analytics

Schedule:

Full time