📋 Job Details at a Glance 📍 Location Hyderabad, India 🏢 Company Wells Fargo 👥 Experience 5+ years 🎓 Qualification 5+ years. Relevant technical / engineering background 📅 Eligible Batch 2023, 2024, 2025, 2026 📄 Job Type Full Time 💰 Salary Not Disclosed 🏢 Industry Fintech 🛠 Key Skills machine learning statistical analysis model validation risk management fraud risk models Lead Quantitative Analytics Specialist at Wells Fargo — Full Details & How to Apply Wells Fargo is seeking a Lead Quantitative Analytics Specialist in Hyderabad, India , primarily focusing on validating AI/ML models for fraud risk management . This role requires 5+ years of experience and direct involvement in model validation and risk assessment activities. This position is critical for ensuring the integrity of fraud risk models used in financial transaction monitoring. The role involves leading technical activities in statistical analysis , machine learning , and model validation to assess the performance and reliability of risk models. These activities directly support the detection and prevention of fraudulent activities in real-time transaction systems. The job posting specifies that this is a Wells Fargo role focused on fraud risk models , requiring expertise in statistical analysis and machine learning . The team operates in a technical environment where model validation and risk assessment are core responsibilities. The role is part of Wells Fargo recruitment for technical specialists in the fintech domain. 2023, 2024, 2025, 2026 graduates are eligible. Candidates must have 5+ years. Relevant technical / engineering background and 5+ years experience . The salary is Not Disclosed . Candidates will gain hands-on experience with machine learning , statistical analysis , model validation , and risk management . This role provides a foundation for advancing into senior analytics or risk engineering roles within financial technology systems. 📊 Role Difficulty: Medium | Competition Level: High | Fresher Friendly: No NexisGrow.com features this opportunity as part of its curated tech job listings. All details are sourced from the official job posting. Apply online before the opportunity closes. Job Role & Responsibilities The Lead Quantitative Analytics Specialist at Wells Fargo is responsible for identifying and quantifying model risk in financial fraud detection systems, ensuring compliance with regulatory risk standards through rigorous model validation processes. This role directly impacts the accuracy of fraud risk models used in real-time transaction monitoring. Lead complex activities to identify and quantify model risk using statistical analysis and model validation frameworks within the financial fraud space . Utilize machine learning techniques to assess and validate fraud risk models that detect anomalous transaction patterns in real-time payment systems . Collaborate with the Model Risk Management Group to deliver insights on risk management initiatives using statistical theories and model performance metrics . Perform high-quality risk management assessments based on statistical analysis and data analysis of historical fraud incident datasets from Wells Fargo’s transaction logs . Manage and validate both traditional and emerging risk vectors in the financial fraud space using machine learning and model validation protocols. Document and report on model validation processes and results to ensure compliance with regulatory risk standards in Wells Fargo’s internal audit framework . Troubleshoot and solve performance issues in fraud detection models by applying statistical analysis and model validation diagnostics to model output metrics . Develop and maintain fraud risk models using machine learning and statistical analysis to improve detection accuracy in credit card and mobile payment systems . This role requires direct ownership of model validation outcomes , with full accountability for fraud risk model performance and regulatory compliance in Wells Fargo’s financial systems . Required Skills & Technical Competencies The Lead Quantitative Analytics Specialist must possess a strong foundation in machine learning , statistical analysis , model validation , and fraud risk models to execute technical tasks in financial fraud detection systems at Wells Fargo . Technical Skills Machine learning — advanced — used to develop and validate fraud risk models in real-time transaction monitoring systems using supervised classification algorithms like XGBoost and Random Forest. Statistical analysis — advanced — applied to quantify model risk and assess performance metrics such as AUC, precision, recall, and false positive rate in fraud detection datasets . Model validation — advanced — implemented to ensure fraud risk models meet regulatory risk standards and pass internal audit validation checks using backtesting and stress testing protocols. Risk management — advanced — used to evaluate and mitigate financial fraud risks across credit card and digital banking platforms using risk exposure metrics and scenario analysis . Fraud risk models — advanced — directly applied to build, test, and deploy predictive models that detect anomalous behavior in payment transaction data from Wells Fargo’s core systems . When preparing your resume or interview response, emphasize hands-on experience with machine learning and statistical analysis in fraud detection using real-world financial datasets and model validation frameworks . Eligibility Criteria This role is designed for candidates with a technical or engineering background and over 5 years of relevant experience in quantitative analytics or financial risk modeling . Must hold a degree in Computer Science, Statistics, Engineering, or a related technical field with a minimum CGPA of 3.0 or equivalent. Eligible batches are 2023, 2024, 2025, and 2026 only. Minimum of 5 years of professional experience in machine learning , statistical analysis , or financial risk modeling is required. Experience must be directly related to fraud detection models or model validation in financial or transactional systems. Must have a portfolio demonstrating machine learning or statistical analysis projects related to risk modeling or fraud detection . Only candidates with a technical engineering or data science background and proven experience in model validation are eligible. Documentation & Portfolio Requirements Your resume must include a clear section on machine learning and statistical analysis projects, with specific metrics such as precision, recall, AUC , and model validation outcomes from real-world datasets. For this role, prioritize showcasing a portfolio that includes fraud risk model development using machine learning and statistical analysis , with documented performance metrics and validation results from financial transaction data. Salary for Lead Quantitative Analytics Specialist at Wells Fargo 💰 Compensation Not Disclosed The advertised compensation for the Lead Quantitative Analytics Specialist role at Wells Fargo is Not Disclosed . The exact in-hand figure and any additional components are confirmed by the company during the offer or HR discussion stage. Recommended Courses & Preparation Tips for Lead Quantitative Analytics Specialist Upskilling with the right resources significantly enhances your chances of selection for this specialized role in quantitative analytics. Recommended Courses & Resources machine learning — Essential for developing predictive models and algorithms relevant to this role. statistical analysis — Crucial for interpreting data and validating models effectively. KodNest — Provides practical experience in quantitative methods and analytics. Boost your profile with relevant certifications at NexisGrow GetCertified — strengthen your application before you apply. Common Mistakes to Avoid ❌ Applying without demonstrating experience in model validation or machine learning — ensure to provide specific examples. ❌ Using a generic resume instead of tailoring it to the specific responsibilities outlined in the job description — customize your resume for better alignment. ❌ Listing technologies like machine learning without detailing how they were applied in previous roles or projects — provide context and examples. ❌ Ignoring the requirement for over 5 years of experience — ensure your experience meets this critical requirement. ❌ Adding unrelated skills or unsupported claims to increase ATS keywords — focus on relevant skills only. ❌ Failing to verify the official Apply URL and job details before submission — always double-check before applying. Before You Apply — Checklist ✅ Confirm the job title, company, location, work mode, and experience requirement. ✅ Check that the candidate meets the supplied qualification criteria. ✅ Verify eligibility against the supplied eligible batches and experience requirement. ✅ Add relevant supplied JD keywords naturally to the resume. ✅ Highlight projects or experience related to the supplied technologies and responsibilities. ✅ Remove unsupported technologies, achievements, or experience claims. ✅ Open and verify the supplied Apply URL before submitting the application. ✅ Save the job details, application date, and role-specific resume version for tracking. Resume Tailoring & ATS Keywords for Lead Quantitative Analytics Specialist Optimizing your resume for ATS is crucial for ensuring your application gets noticed for this specialized role. ATS Keywords to Include machine learning statistical analysis model validation risk management fraud risk models quantitative analytics data analysis AI model risk financial fraud business initiatives technical reporting Resume Tips for This Role Highlight your experience with machine learning and statistical analysis prominently on your resume. Emphasize any relevant projects or roles where you utilized model validation or risk management techniques. Consider showcasing a project that involved fraud detection or risk assessment using machine learning . Use exact keywords from the job description to align your resume with the ATS requirements. Avoid including unsupported claims or technologies that you cannot substantiate. Build an ATS-optimized resume for this role using NexisGrow Resume Builder — free for all job seekers. Pro tip: Avoid including unrelated skills or unsupported claims in your resume for this role. How to Apply for Lead Quantitative Analytics Specialist at Wells Fargo Apply Now — Wells Fargo Open the official Apply URL and confirm the job title and company matches the position you're applying for. Prepare a resume that aligns with the required skills, responsibilities, qualifications, and experience outlined in the job posting. Complete the official application form accurately, ensuring all information is truthful and avoiding unsupported claims. Submit the application and save the confirmation or application reference number if provided by the portal. Record the application date and monitor the official company portal or your registered email for updates. Applications are reviewed on a rolling basis — early submission is recommended. Apply Now — Wells Fargo NexisGrow.com does not charge any fees for job applications. Wells Fargo Wells Fargo is a fintech company based in Hyderabad, India , operating in a financial services environment. This Lead Quantitative Analytics Specialist role is onsite and works within the Model Risk Management Group, focusing on fraud risk models and advanced analytics. The team validates fraud detection models using machine learning , statistical analysis , and risk management techniques. Responsibilities include model testing, validation, documentation, and risk assessment across business processes to ensure robust and reliable fraud detection systems. This role supports Wells Fargo ’s fraud risk management practices by validating AI/ML models and ensuring model integrity. It enables early-career professionals to gain hands-on experience in model validation and risk assessment using machine learning and statistical methods. The role offers early-career exposure to machine learning , statistical analysis , and risk management through real-world model validation and fraud risk assessment, building foundational expertise in data-driven risk practices. Company Details Industry Fintech Location Hyderabad, India Connect With Us Careers Apply Now Website 🔗 wf.wd1.myworkdayjobs.com Frequently Asked Questions Interview · Role · Salary · Growth ? Who can apply for this role? Eligibility Tap to expand + Answer Candidates with a relevant technical background and over 5 years of experience, from the eligible batches of 2023, 2024, 2025, and 2026. ? What technical skills are most important for this role? Skills Tap to expand + Answer Machine learning, statistical analysis, model validation, risk management, and fraud risk models. ? What is the expected salary for this position? Salary Tap to expand + Answer Salary Display: Not Disclosed. ? What should I expect after applying? Hiring Process Tap to expand + Answer The exact hiring stages are not specified in the job posting. ? How should I prepare for the interview? Preparation Tap to expand + Answer Review machine learning concepts, understand statistical analysis techniques, prepare examples of model validation, familiarize yourself with risk management practices, and be ready to discuss fraud detection strategies. ? Is this role remote, hybrid, or onsite? Work Mode Tap to expand + Answer This role is onsite in Hyderabad, India. ? What career exposure can this role provide? Growth Tap to expand + Answer Exposure to advanced analytics, risk management practices, and collaboration with the Model Risk Management Group. ? What should I highlight in my resume for this role? Resume Tap to expand + Answer Emphasize skills in machine learning, statistical analysis, model validation, and relevant project experience. ? Is there a last date to apply? Application Tap to expand + Answer Not specified in the job posting. ? Is there a probation period? Probation Tap to expand + Answer Not specified in the job posting. ? What is the work environment like for this role? Culture Tap to expand + Answer The role involves collaboration with the Model Risk Management Group and requires onsite presence. ? Can freshers apply for this role? Fresher Tap to expand + Answer No, the role requires over 5 years of experience. 🔗 Explore More on NexisGrow More jobs in Hyderabad Browse all Tech jobs Latest Fresher jobs More jobs at Wells Fargo Work From Home jobs Ready to Apply? Don't Miss This Opportunity! Apply only via the official link. NexisGrow.com charges zero application fees. 👉 Apply Now — Official Link NexisGrow.com does not charge any application or registration fees. Beware of fraudulent offers. Naukri ki baat, NexisGrow ke saath • NexisGrow.com