Internal Audit Senior Analyst, Data Analytics

We need to output HTML fragment with sections: headings

for sections like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections that have real specific content. Remove boilerplate, navigation, EEO, etc. Keep substantive info. We need to parse the posting. Key sections: - About Salesforce (intro) maybe "About the role"? Actually "About Salesforce" is description of company. Could be "About the role"? The instruction: use

for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we can map content accordingly. We have: - The Opportunity: description of role (Internal Audit Senior Analyst). Could be "About the role" or maybe "Responsibilities"? Actually "The Opportunity" is overview. Could be "About the role". We'll put that as

About the role

with paragraph. - What You'll Do: list of duties. That's responsibilities. Use

• . - You're Our Person If...: list of qualifications/requirements. Could be "Requirements" or "Qualifications". We'll separate maybe "Requirements" for mandatory, "Qualifications" for preferred? The posting has "You're Our Person If..." with bullet list of required experience/skills. Then "Even Better If..." for preferred. So we can have

  Requirements

  with list of required items, and

  Qualifications

  with list of preferred items (Even Better If...). Or we could combine but instruction: prefer few substantive sections over many thin ones. But we have distinct content. Could make one section "Requirements and Qualifications" but better to separate as they are distinct. - Skills: maybe we can extract skills from requirements: SQL, Python, Tableau, AI/ML, etc. But we already have them in requirements. Could still have a Skills section summarizing. But to avoid thin sections, maybe we incorporate skills into Requirements. - Benefits: posting mentions benefits at end: "Salesforce offers a variety of benefits to help you live well including: time off programs, medical, dental, vision, mental health support, paid parental leave, life and disability insurance, 401(k), and an employee stock purchasing program." Also earlier: "Unleash Your Potential When you join Salesforce, you’ll be limitless..." but that's fluff. So we have benefits specifics. So we can include

  Benefits

  with
  • list. - Pay: not specified. No salary info. So we should NOT include Pay section. - Schedule: mentions "3 days per week hybrid schedule." Also location: Indianapolis, IN office but will also consider Atlanta, GA office. That's schedule/location. So we can include

    Schedule

    with paragraph about hybrid schedule and location. - Also there is "Location" line. Could be part of Schedule. We must not include boilerplate like "To get the best candidate experience..." etc. Also remove "Accommodations", "Posting Statement", EEO, etc. We must preserve all substantive information. So we need to keep details like: - Role: Internal Audit Senior Analyst. - Opportunity description: design and deliver AI and analytics solutions that support Internal Audit engagements end to end, from scoping and data extraction through analysis, visualization, and reporting. Work directly with audit teams across full audit life-cycle (risk assessment, planning, execution, and reporting), building AI logic, SQL queries, Python scripts, and Tableau dashboards that make the audit process more defensible. Experience with SQL and AI/ML, hands-on use of AI and AI coding tools as well prior audit and related experience to accelerate analysis, documentation, and work paper development, plus some administration of the team's audit tooling. - What You'll Do bullet list (we need to preserve each bullet). Let's extract them: 1. Partner with Internal Audit teams throughout the audit lifecycle, building and applying the right solutions and capabilities. 2. Develop optimized SQL queries and AI system prompts (.md) to seamlessly extract, profile, and reconcile high-volume data from financial, operational, and source platforms. 3. Build Python and other scripts for data cleaning, transformation, and repeatable audit testing (e.g., exception testing, continuous assurance/monitoring). 4. Use AI tools and other capabilities to speed up data analysis, summarize findings, draft work papers, and build lightweight internal tooling. 5. Design clear, audit-ready visualizations and dashboards in Tableau that communicate risk and findings to both technical and non-technical stakeholders. 6. Develop a working understanding of the business systems in scope (e.g., ERP, CRM, ticketing, HR, or financial systems) well enough to assess data lineage, controls, and where risk actually lives. 7. Provide light system administration support for the team's GRC and other tooling, including user access, workflow/queue configuration, and basic troubleshooting. 8. Proactively identify AI and analytics opportunities and process gaps rather than waiting to be asked, flag risk trends, data quality issues, and automation opportunities as you see them. 9. Support training and enablement for audit staff on analytics tools, dashboards, and AI-assisted workflows so the broader team can self-serve. 10. Document methodology, assumptions, and results so analytics can be re-run, reviewed, and defended by audit leadership and external reviewers. - Requirements (You're Our Person If...): Bullet list: - 2–4 years of experience in AI, Agentic AI, data analytics, audit analytics, business intelligence, or a related analytical role. (any or all of the following: Claude/Cursor, Tableau, Snowflake, Python) - 1–2 years of experience in audit, internal audit, risk security or a related field - Experience building and deploying production-grade LLM systems, including agents, tool integration, MCP, retrieval/grounding, and prompt optimization. You know what it takes to monitor and scale real AI workflows. - Strong principles around agent engineering, from tool scoping and grounded reasoning to safe failure handling and continuous model evaluation. - Strong proficiency in SQL for querying and manipulating large, complex datasets. - Working proficiency in Python for data analysis and scripting. - Capability to use probabilistic models and tune to behave as deterministically as possible for audit-defensible results. - Experience building dashboards or reports in Tableau (or a comparable BI tool). - Demonstrated ability to learn business systems and processes quickly, gather business requirements directly from stakeholders, and reason about data flow, controls, and risk. - A proactive, self-starting approach to identifying and solving problems, not just executing assigned tasks. - Comfort with basic system administration tasks (user access, configuration) on business platforms such as an eGRC tool. - Strong written and verbal communication skills, including the ability to train and enable non-technical colleagues on new tools and workflows. - Bachelor's degree in a quantitative, business, accounting, or related field, or equivalent practical experience. - Even Better If... (preferred qualifications): - Prior experience in internal audit, external audit, risk management, or compliance analytics. - Hands-on administration experience with an GRC platform - Familiarity with control frameworks (e.g., COSO, SOX). - Experience with additional analytics or automation tools. - Exposure to Salesforce's own platform and data model. - Location: Indianapolis, IN office but will also consider Atlanta, GA office. 3 days per week hybrid schedule. - Benefits: list as above. We also have some fluff about "Unleash Your Potential..." but we can keep as part of Benefits or maybe a short paragraph about culture? But we should not include filler. The benefits section already captures specifics. The "Unleash Your Potential" is generic marketing; we could omit as it's not specific benefit. However we might keep a short paragraph about culture? The instruction: preserve ALL substantive information; do NOT invent or summarize away detail. The "Unleash Your Potential" is substantive? It's vague but still part of posting. However it's basically fluff; but it's still part of the posting. The instruction says remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. This is not those. It's marketing copy. Might be considered substantive? It's not specific info like benefits, but it's still part of the job description. However we can keep it as a short paragraph under maybe "About the role" or separate? But we already have About the role covering opportunity. The "Unleash Your Potential" could be considered part of Benefits or culture. To be safe, we could include a short paragraph under Benefits after the list, but it's not a benefit per se. Might be considered filler. I'd lean to omit it because it's not specific benefit, and we prefer few substantive sections. The instruction: "Prefer a few substantive sections over many thin ones." So we can combine benefits and maybe culture into Benefits section. Thus final HTML:

    About the role

    Internal Audit Senior Analyst to design and deliver AI and analytics solutions that support Internal Audit engagements end to end, from scoping and data extraction through analysis, visualization, and reporting. You'll work directly with audit teams across the full audit life-cycle (risk assessment, planning, execution, and reporting), building AI logic, SQL queries, Python scripts, and Tableau dashboards that make the audit process more defensible. This role calls for experience with SQL and AI/ML, hands-on use of AI and AI coding tools as well prior audit and related experience to accelerate analysis, documentation, and work paper development, plus some administration of the team's audit tooling.

    But need to ensure we preserve all details: maybe split into two paragraphs? Could keep as one. Then Responsibilities:

    Responsibilities

    • Partner with Internal Audit teams throughout the audit lifecycle, building and applying the right solutions and capabilities.
    • Develop optimized SQL queries and AI system prompts (.md) to seamlessly extract, profile, and reconcile high-volume data from financial, operational, and source platforms.
    • Build Python and other scripts for data cleaning, transformation, and repeatable audit testing (e.g., exception testing, continuous assurance/monitoring).
    • Use AI tools and other capabilities to speed up data analysis, summarize findings, draft work papers, and build lightweight internal tooling.
    • Design clear, audit-ready visualizations and dashboards in Tableau that communicate risk and findings to both technical and non-technical stakeholders.
    • Develop a working understanding of the business systems in scope (e.g., ERP, CRM, ticketing, HR, or financial systems) well enough to assess data lineage, controls, and where risk actually lives.
    • Provide light system administration support for the team's GRC and other tooling, including user access, workflow/queue configuration, and basic troubleshooting.
    • Proactively identify AI and analytics opportunities and process gaps rather than waiting to be asked, flag risk trends, data quality issues, and automation opportunities as you see them.
    • Support training and enablement for audit staff on analytics tools, dashboards, and AI-assisted workflows so the broader team can self-serve.
    • Document methodology, assumptions, and results so analytics can be re-run, reviewed, and defended by audit leadership and external reviewers.
    Then Requirements:

    Requirements

    • 2–4 years of experience in AI, Agentic AI, data analytics, audit analytics, business intelligence, or a related analytical role. (any or all of the following: Claude/Cursor, Tableau, Snowflake, Python)
    • 1–2 years of experience in audit, internal audit, risk security or a related field
    • Experience building and deploying production-grade LLM systems, including agents, tool integration, MCP, retrieval/grounding, and prompt optimization. You know what it takes to monitor and scale real AI workflows.
    • Strong principles around agent engineering, from tool scoping