Senior Data Scientist - Fraud

Posted 3 Days Ago
30005, Alpharetta, GA, USA
In-Office
Senior level
Fintech • Consulting
The Role
Lead design, development, and productionization of advanced fraud and credit risk models (including GenAI/LLM solutions). Analyze internal and external data, build algorithms to improve data governance and quality, mentor junior staff, present insights to leadership, and drive analytical strategy across global teams.
Summary Generated by Built In

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.

Equifax Enterprise Innovation Office is seeking a strong Data Scientist who can utilize subject matter expertise of data structures, analytics, algorithms/models, and strong computer science fundamentals to lead data preparation, analytics, and development of deployable solutions across multiple projects in the Fraud space.

Qualified candidates will have a passion for data science, mathematics, statistics, AI/Machine learning, data gathering, and experience in financial modeling. The ideal candidate will come from a fraud background, deeply understanding the importance of fraud in the credit data space.

We believe great things happen when teams connect. Our schedule is built around 4 days of high-impact, in-office collaboration (Monday–Thursday), paired with Friday Flexibility to wrap up your week remotely.

This role reports to our office Alpharetta, GA office.

This position does not offer immigration sponsorship (current or future) including F-1 STEM OPT extension support.

This is a direct-hire role and is not open to C2C or vendors.

What you’ll do

  • Design and deploy advanced fraud and credit risk models to mitigate threats across the enterprise.

  • Develop and productionize innovative GenAI and LLM-driven solutions for complex fraud detection.

  • Develop customer fraud models with exposure to various fraud types (e.g., account takeover, identity theft, payment fraud).

  • End-to-end design, development, and deployment of advanced machine learning, AI, and Generative AI models to power new product initiatives across the enterprise.

  • Design and build novel algorithms to enhance our data governance, quality, and metadata management capabilities, creating new ways to automatically know and manage our data assets.

  • Proactively collect, analyze, and interpret existing internal data and evaluate new, external data sources to identify and propose new product opportunities for our business units.

  • Act as a senior technical consultant and partner to global teams, helping them frame their business problems, identify data-driven solutions, and overcome their most complex analytical challenges.

  • Serve as a technical leader and mentor for junior data scientists and analysts, conducting code reviews, sharing best practices, and fostering a culture of innovation and excellence.

  • Translate complex analytical findings and research outputs into clear, compelling presentations and strategic recommendations for diverse stakeholders, including senior leadership.

  • Lead the development or projects with multiple deliverables, leveraging business and technical expertise.  

  • Lead the analytical strategy on critical technical capabilities for global company solutions.

  • Work with key stakeholders to support development of proprietary analytical products and custom scores, effectively communicating the "so what" of the analysis using strong data visualizations and business language.

  • Contribute to the evaluation of external data sources and data science capabilities, providing due diligence recommendations.

What experience you need 

  • A Master’s or Ph.D. in Computer Science, Statistics, Mathematics, or a related quantitative field

  • 7-10+ years of hands-on experience building and deploying production-level data science solutions using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, 

  • Proficient skills building models using packages including scikit learn, XGBoost, Tensorflow, PyTorch, Transformers, etc.

  • 4+ years of experience in Python and its core data science libraries (e.g., Pandas, NumPy, Scikit-learn, PyTorch, TensorFlow)

  • 4+ years of experience to work with massive (petabyte-scale) datasets using strong SQL and big data technologies (e.g., Spark, Dataflow, BigQuery, Snowflake) within a cloud environment (AWS, GCP-Preferred).

  • Deep knowledge of classical machine learning, statistical modeling, and NLP. You should have a strong command of supervised and unsupervised learning, time-series analysis, and model validation techniques

  • Excellent verbal and written communication skills, with a proven ability to collaborate effectively with cross-functional teams and present complex topics to non-technical audiences

  • 1+ year of experience mentoring junior data scientists

  • 2+ years’ experience developing and leading the technical vision of an organization and working independently and closely with senior leadership to lead data science to continued success into the future

  • Experience with development and deployment of models in a cloud-based environment such as AWS or GCP.

  • Background in, and an innate talent and passion for, trying new technologies and quickly assessing value and implementability within organizations.

  • Hunger for innovation and ability to switch between multiple projects at once.

What could set you apart

  • Extensive experience in developing and deploying production-level Fraud and Credit risk models.

  • Extensive experience in building, fine-tuning, and productionizing GenAI and LLM solutions (e.g., RAG, fine-tuning, LLM orchestration).

  • Demonstrable, hands-on experience building and fine-tuning LLMs, developing Retrieval-Augmented Generation (RAG) systems, and understanding the MLOps lifecycle for GenAI.

  • Prior experience working in the financial services industry (e.g., risk modeling, algorithmic trading, fraud detection, or compliance).

  • A portfolio or past experience building models specifically for data management (e.g., data quality anomaly detection, PII identification, automated data cataloging).

  • A history of publishing research in relevant AI/ML conferences or contributing to major open-source data science projects.

  • Knowledge in graph mining and graph data model

  • Innate talent and passion for trying new technologies and quickly assessing value and implementability within organizations.

  • Demonstrable experience with identity graphs and graph-related technologies is a plus.

#LI-AM2
#LI-Hybrid

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-Atlanta JV White

Function:

Function - Data and Analytics

Schedule:

Full time

Skills Required

  • Master's or Ph.D. in Computer Science, Statistics, Mathematics, or related quantitative field
  • 7-10+ years building and deploying production-level data science solutions using advanced ML algorithms
  • Experience with scikit-learn, XGBoost, TensorFlow, PyTorch, Transformers
  • 4+ years Python with core data science libraries (Pandas, NumPy, Scikit-learn, PyTorch, TensorFlow)
  • 4+ years working with massive (petabyte-scale) datasets using SQL and big data technologies (Spark, Dataflow, BigQuery, Snowflake)
  • Experience deploying models in cloud environments (AWS or GCP; GCP preferred)
  • Deep knowledge of classical machine learning, statistical modeling, NLP, time-series analysis, and model validation
  • Experience developing and productionizing GenAI/LLM solutions, including RAG and fine-tuning
  • 1+ year mentoring junior data scientists
  • 2+ years developing and leading technical vision and working with senior leadership
  • Strong verbal and written communication and stakeholder presentation skills
  • Background or experience in fraud and credit risk modeling (account takeover, identity theft, payment fraud)
  • Experience with graph mining, identity graphs, or graph-related technologies
  • History of publishing research or contributing to major open-source data science projects

Equifax Inc. Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Equifax Inc. and has not been reviewed or approved by Equifax Inc..

  • Retirement Support Savings programs include a 401(k) with company matching and, in some contexts, profit-sharing or pension components. These are described as solid parts of the total package.
  • Parental & Family Support Programs include paid parental leave for birth and non-birthing parents and adoption assistance. Company materials highlight these benefits as part of a family-supportive offering.
  • Flexible Benefits Multiple medical plan choices, dental and vision options, FSAs/HSAs, and voluntary supplemental coverages enable customization. The company publishes plan summaries and SPDs to help compare cost and coverage by location and tier.

Equifax Inc. Insights

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The Company
HQ: Atlanta, GA
16,742 Employees

What We Do

At Equifax (NYSE: EFX), we believe knowledge drives progress. As a global data, analytics, and technology company, we play an essential role in the global economy by helping financial institutions, companies, employers, and government agencies make critical decisions with greater confidence. Our unique blend of differentiated data, analytics, and cloud technology drives insights to power decisions to move people forward. Headquartered in Atlanta and supported by nearly 15,000 employees worldwide, Equifax operates or has investments in 24 countries in North America, Central and South America, Europe, and the Asia Pacific region. For more information, visit Equifax.com.

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