Lead Data Engineer - Data Scientist

We need to output HTML fragment with sections: About the role (description), Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections if posting has real specific content. We must not repeat job title. Must not include Job ID etc. Must preserve all substantive info. Remove boilerplate like AI insights, EEO, etc. Also remove duplicated lines. Must not include sections with placeholder text like "commensurate with experience". Pay and Schedule: posting includes Pay Range and maybe schedule? Not explicit schedule. It says "This role is NOT eligible for 100% remote work". That's about remote work, not schedule. No explicit schedule like full-time, part-time. So we should not create Schedule section unless posting states it. Benefits: posting lists benefits. So include Benefits section. Pay: posting includes Pay Range. So include Pay section. About the role: we have description paragraphs. Responsibilities: we have bullet-like sentences under "In This Role, You Will". Those are responsibilities. Requirements: maybe "Required Qualifications". Qualifications: "Desired Qualifications". Skills: maybe combine required/desired? But we can separate: Required Qualifications, Desired Qualifications, Skills? The instruction says use headings for section headings like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We need to decide which to include based on content. We have About the role (description). Responsibilities (the list). Requirements (maybe Required Qualifications). Qualifications (Desired Qualifications). Skills (maybe list of skills like Python, etc). Could combine but better to separate. However we must not create thin sections. Let's see content: Required Qualifications: 5+ years Database Engineering, 5+ years Python data science libraries, exposure to deep learning framework. Desired Qualifications: many items: Vertex AI, GCP, BigQuery, graph networks, learning mindset, Github, Power BI, Tableau, Alteryx, software engineering fundamentals, math foundations, model evaluation, AI coding agents, LLMs, RAG, AI agents, strong SQL, book-of-work management, hands-on ability, confident producer, communicator, Bachelor/Master's degree. That's a lot. Could treat as Qualifications. Skills maybe overlapping. But we can put Required Qualifications under Requirements heading, Desired Qualifications under Qualifications heading, and maybe Skills under Skills heading (like specific technical skills). However many of those are skills. To avoid duplication, we could combine Required and Desired into Qualifications and not have separate Skills. But instruction says we can include sections only when posting has real specific content. We have content for Requirements (Required Qualifications). We have content for Qualifications (Desired Qualifications). We could also have Skills (maybe list of specific skills like Python, Pandas, NumPy, Scikit-Learn, TensorFlow/PyTorch, SQL, etc). But those are already in Required Qualifications. Might be redundant. Safer to include Requirements and Qualifications sections, and maybe Skills not needed. Benefits and Pay we have. About the role we have. Responsibilities we have. So final sections: About the role, Responsibilities, Requirements, Qualifications, Benefits, Pay. No Schedule. Now we need to format:

About the role

then

with prose (the description). Then

Responsibilities

then

• each responsibility. Then

  Requirements

  then
  • each required qualification. Then

    Qualifications

    then
    • each desired qualification. Then

      Benefits

      then
      • each benefit. Then

        Pay

        then

        with pay range. We must preserve all substantive info, not invent or summarize away detail. Must not include boilerplate like AI insights, EEO, etc. Also remove duplicated lines (like the AI insights repeated at top). Also remove location list? Location is substantive? It's location of job. Should we include? The instruction says we can include location maybe as part of About the role? Not specified heading. Could include as a

        under About the role? But location is not a heading. We could include location as a short

        after About the role before Responsibilities? But we must not create extra headings. The instruction: "Do NOT repeat the job title as a heading (the page already shows it) and do NOT put Job ID / requisition numbers as headings — fold minor metadata into a short

        or drop it." Location is minor metadata? Could be folded into a short

        . Probably we should include location as a short paragraph after About the role? But we already have About the role prose; we could append location info there. However we must preserve ALL substantive information. Location is substantive. So we need to include it somewhere. Could add a

        after About the role: "Locations: 300 S Brevard, Charlotte, North Carolina 28202; 401 Las Colinas Blvd W Bldg. A - Irving, TX 75039; 550 S 4th St. Minneapolis, MN 55415; 3075 Loyalty Cir. - Columbus, Ohio 43219". That preserves. Also we have "Posting Statements" etc like "Job posting may come down early due to volume of applicants." That's minor metadata; could fold into short

        or drop. Probably drop as it's not essential. Also "Required location(s) listed above. Relocation assistance is not available for this position" etc. That's also metadata. Could fold into short

        after location? But we already have location. Could include a short

        about relocation assistance not available, visa sponsorship not eligible, remote work not 100%, posting may come down early. That's substantive? Might be considered metadata but still info. The instruction: "fold minor metadata into a short

        or drop it." So we can include a short

        with those statements. Also "Pay Range Reflected is the base pay range offered for this position. Pay may vary depending on factors including but not limited to demonstrated examples of prior performance, skills, experience, or work location. Employees may also be eligible for incentive opportunities." That's part of Pay section; we can include in

        after pay range. Also "Benefits Wells Fargo provides eligible employees with a comprehensive set of benefits, many of which are listed below. Visit Benefits - Wells Fargo Jobs for an overview of the following benefit plans and programs offered to employees." That's intro; we can include as

        before list. Now we must not include EEO, equal opportunity, scam-warning, etc. Remove those. Now construct HTML. Let's list responsibilities from "In This Role, You Will" sentences: - Lead complex initiatives with broad impact and act as key participant in large scale software planning for the Identity and Access management. - Design, develop, and run tooling to discover problems in data and applications and report the issues to engineering and product leadership - Apply knowledge of statistical and data science methods and techniques to business problems relating to Identity and Access Management. - Serve as a subject matter expert on ML, AI and the application of mathematical and statistical techniques to large datasets. - Design, support and operate data pipelines, data models, dashboards, and API integrations to deliver real-time and batch analytics use cases. - Design and conduct experiments, statistical analyses, and hypothesis testing to evaluate proposals in support of controls, policies, and operational processes. - Build AI-powered capabilities that identify inappropriate access, recommend entitlements before users request them, and detect anomalous behavior across millions of identity events. - Lead other IAM team members including operations, onboarding, initiatives and engineering teams as well as line of business and lines of defense teams to understand analytical needs and translate them into technical solutions. - Establish and implement engineering and analytical best practices when developing solutions. - Develop solutions in accordance with established security, privacy, model risk, and regulatory guidelines. - Develop, test, deploy and support of ML-enabled analytical solutions and guide other members of the team in ML, AI and statistical techniques in driving adoption of AI/ML across IAM. - Assist in monitoring model health, reliability, and drift to ensure continuous improvement and required remediation. - Demonstrate proficiency in using AI-assisted development and analysis tools (e.g., GitHub Copilot and approved code-centric agents) - Leverage AI to accelerate system design, coding, testing, analysis, and troubleshooting - Apply strong technical judgment when validating and integrating AI-assisted outputs into solutions - Understand and account for model limitations, security risks, and operational considerations - Apply AI responsibly in development and production environments - Ensure AI usage aligns with security, compliance, privacy, and ethical standards That's many items. We'll keep them as

      • . Now Required Qualifications: - 5+ years of Database Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education - 5+ years of experience with Python data science libraries such as Pandas, NumPy, and Scikit-Learn, together with exposure to a deep learning framework such as TensorFlow or PyTorch That's it. Desired Qualifications (list): - Knowledge of Vertex AI, GCP environments, BigQuery and getting models into production on these platforms - Knowledge of graph networks for anomaly detection (Neo4j) - A learning mindset that keeps up-to-date with the latest developments in the field - Knowledge of Github for code management, Power BI, Tableau, Alteryx - Understanding of software engineering fundamentals including testing, debugging, code reviews etc is highly desirable - Knowledge of the mathematical foundations of statistics, machine learning, and modern AI techniques. - Strong understanding of model evaluation techniques, particularly for classification and clustering models including metrics such as precision, accuracy, F1-scores, confusion matrices, ROC curves etc. - High level of comfort with the use of AI coding agents such as Github Copilot, Claude Code, Cursor, Devin or others with the ability to critically examine AI code for fitness for use. - Familiarity with LLMs, RAG, and AI agents - Strong SQL skills and ability to work with relational and analytical databases. - Strong book-of-work management and organizational skills. - Hands-on ability to manipulate data and tools to prototype and present solutions. - Confident and self-motivated producer of original ideas and solutions, with sound judgment for when to escalate issues - Strong written and verbal communicator with excellent presentation skills - Ability to communicate complex technical concepts to colleagues and team members. - Bachelor's or Master's degree in Computer Science, Data Science, AI, Engineering, or related field. Now Benefits list (from posting): - Health benefits - 401(k) Plan - Paid time off - Disability benefits - Life insurance, critical illness insurance, and accident insurance - Parental leave - Critical caregiving leave - Discounts and savings - Commuter benefits - Tuition reimbursement - Scholarships for dependent children - Adoption reimbursement Now Pay: range $119,000.00 - $206,000.00 plus note about base pay range, may vary, incentive opportunities. Now About the role prose: The description paragraphs: "About this role: Wells Fargo is seeking a Lead Data Engineer in Cybersecurity as part of Identity Access Management. Learn more about career areas and business divisions at wellsfargojobs.com This role sits at the intersection of cybersecurity, data science, machine learning, and AI. The successful candidate will develop intelligent solutions that improve access governance, identify anomalous behavior, automate entitlement decisions, and generate actionable insights across Wells Fargo's Identity and Access Management ecosystem." We can combine into a paragraph. Now location paragraph: "Locations: 300 S Brevard, Charlotte, North Carolina 28202; 401 Las Colinas Blvd W Bldg. A - Irving, TX 75039; 550 S 4th St