Fraud AI / Data Managing Consultant (remote)

We need to output only HTML fragment with sections: headings

for sections like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We must include only sections that have real specific content. Must not repeat job title. Must not include Job ID etc. Must preserve all substantive info. Remove boilerplate. We need to parse the posting. Key parts: - Job Family Technology Consulting Travel Required Up to 50% Clearance Required Ability to Obtain Public Trust (these are metadata; we can fold into a short

maybe under About the role? Actually "Job Family Technology Consulting Travel Required Up to 50% Clearance Required Ability to Obtain Public Trust". Could be a short paragraph. - "What You Will Do The AI/Data Managing Consultant leads discrete workstreams and delivers advanced AI and data solutions. This role combines technical depth, client engagement, and mentorship of junior team members while driving real‑world AI adoption." This is description. - Then "Key Responsibilities" list bullet points. - Then "What You Will Need" list of requirements. - Then "What Would Be Nice To Have" list of nice-to-have. - Then salary range: "The annual salary range for this position is $130,000.00-$216,000.00. Compensation decisions depend on a wide range of factors..." - Then "What We Offer Guidehouse offers a comprehensive, total rewards package..." then bullet list of benefits. - Then "About Guidehouse" includes EEO etc which we should remove (boilerplate). Also the accommodation info etc is boilerplate; we should remove. Thus sections: - About the role (maybe combine job family and description). Could have a short paragraph. - Responsibilities (list) - Requirements (must have) (list) - Nice-to-have (maybe Skills? Actually "What Would Be Nice To Have" could be Skills or Qualifications. We'll treat as "Preferred Qualifications" or "Skills". The instruction says use headings like Skills, Benefits, Pay, Schedule. We can use "Skills" for nice-to-have. Or "Qualifications" for must-have. Let's decide: Use "Requirements" for must-have, "Preferred Qualifications" for nice-to-have. But headings list includes Qualifications, Skills. We can use "Qualifications" for must-have and "Skills" for nice-to-have. Or we could use "Requirements" not in list but it's allowed? The instruction says use

for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). It says e.g., meaning those are examples; we can use others? Probably better to stick to those examples. So we can use About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay. Schedule not present. Thus: -

About the role

: paragraph with job family, travel, clearance, public trust, and description. -

Responsibilities

: ul li list of responsibilities. -

Requirements

: ul li list of must-have. -

Qualifications

: maybe we could put nice-to-have here? But Qualifications could be both must and nice? However we already used Requirements for must-have. Qualifications could be nice-to-have. Or we could split: Requirements for must-have, Qualifications for nice-to-have. Let's do that. -

Skills

: maybe we could put technical skills? But we already have them in Requirements and Qualifications. Could combine. But we need to avoid thin sections. Perhaps we can merge Requirements and Qualifications into one section? But instruction says prefer few substantive sections over many thin ones. Could combine Requirements and Qualifications into one "Requirements" section with both must and nice? But then we lose distinction. However we could keep Requirements for must-have and Qualifications for nice-to-have; both are substantive. -

Benefits

: ul li list of benefits. -

Pay

: p with salary range and note about compensation decisions. We should not include Schedule. Now we need to preserve all substantive info. Let's extract details. About the role: - Job Family: Technology Consulting - Travel Required: Up to 50% - Clearance Required: Ability to Obtain Public Trust (must obtain and maintain Federal or DHS "PUBLIC TRUST"; candidates must obtain approved adjudication prior to onboarding; active PUBLIC TRUST or SUITABILITY preferred) - Description: The AI/Data Managing Consultant leads discrete workstreams and delivers advanced AI and data solutions. This role combines technical depth, client engagement, and mentorship of junior team members while driving real‑world AI adoption. We'll combine into a paragraph. Responsibilities list (from Key Responsibilities): - Design and implement scalable AI and data solutions from requirements to deployment - Develop, test, and tune fraud prevention and detection rules in a variety of programming languages - Develop and optimize machine learning models and analytics workflows - Lead data analytics efforts in detecting fraud, waste, abuse, and improper payments and identifying key areas to target for program/payment integrity improvements - Partner with clients to identify AI use cases and translate business needs into solutions - Own client deliverables and contribute to executive‑level presentations - Mentor junior consultants and senior consultants, and review their technical work - Ensure solutions align with governance, security, and responsible AI standards (as applicable) Requirements (What You Will Need): - Must be able to OBTAIN and MAINTAIN a Federal or DHS "PUBLIC TRUST"; candidates must obtain approved adjudication of their PUBLIC TRUST prior to onboarding with Guidehouse. Candidates with an ACTIVE PUBLIC TRUST or SUITABILITY are preferred - Bachelor’s degree - EIGHT (8) or more years of experience in AI, data science, analytics, or engineering - FOUR (4) or more years of experience in a fraud/payment integrity-related role - Experience in Python/R, SQL, and data modeling - Experience with statistical and data analytics - Experience working with various data structure formats (CSV/TXT, JSON, XML, Parquet, etc.) - Experience developing, testing, and validating machine learning and other AI models at scale - Experience with data visualization tools (PowerBI, Tableau, Looker, etc.) - Experience with applying data analytics and artificial intelligence in the financial crime compliance and/or fraud, waste, and abuse prevention space - Travel will be 25-50% for candidates not located in the DMV or NYC area Note: Travel mention appears also in Requirements; we can include. Nice-to-have (What Would Be Nice To Have): - Experience leading small teams of junior resources - Proven ability to communicate complex concepts to non‑technical audiences - Experience owning deliverable workstreams - Experience building fraud and/or fincrime monitoring rules in one or more programming languages - Experience working for or supporting healthcare technology, healthcare business or healthcare process initiatives - Cloud experience (AWS, Azure, GCP) including data and ML services - Experience deploying models into production (MLOps) - Experience with AI platforms (Databricks, Palantir, Vertex AI, SageMaker) - Prior consulting or client‑facing delivery experience - Federal or State Medicaid experience (directly as an employee or in a consulting role), particularly experience with fraud prevention and detection and/or program integrity experience with Medicaid Benefits (What We Offer): - Medical, Rx, Dental & Vision Insurance - Personal and Family Sick Time & Company Paid Holidays - Position may be eligible for a discretionary variable incentive bonus - Parental Leave and Adoption Assistance - 401(k) Retirement Plan - Basic Life & Supplemental Life - Health Savings Account, Dental/Vision & Dependent Care Flexible Spending Accounts - Short-Term & Long-Term Disability - Student Loan PayDown - Tuition Reimbursement, Personal Development & Learning Opportunities - Skills Development & Certifications - Employee Referral Program - Corporate Sponsored Events & Community Outreach - Emergency Back-Up Childcare Program - Mobility Stipend Pay: - The annual salary range for this position is $130,000.00-$216,000.00. - Compensation decisions depend on a wide range of factors, including but not limited to skill sets, experience and training, security clearances, licensure and certifications, and other business and organizational needs. We should not include boilerplate about Guidehouse EEO etc. Now produce HTML fragment. We need to use

for each section heading. Use

• for lists. Use

  for prose. We must not include any extra text outside HTML. Let's craft. Be careful to preserve parentheses etc. We'll output:

  About the role

  Job Family: Technology Consulting. Travel Required: Up to 50%. Clearance Required: Ability to Obtain Public Trust (must obtain and maintain a Federal or DHS "PUBLIC TRUST"; candidates must obtain approved adjudication prior to onboarding; active PUBLIC TRUST or SUITABILITY preferred). The AI/Data Managing Consultant leads discrete workstreams and delivers advanced AI and data solutions. This role combines technical depth, client engagement, and mentorship of junior team members while driving real‑world AI adoption.

  Responsibilities

  • Design and implement scalable AI and data solutions from requirements to deployment
  • Develop, test, and tune fraud prevention and detection rules in a variety of programming languages
  • Develop and optimize machine learning models and analytics workflows
  • Lead data analytics efforts in detecting fraud, waste, abuse, and improper payments and identifying key areas to target for program/payment integrity improvements
  • Partner with clients to identify AI use cases and translate business needs into solutions
  • Own client deliverables and contribute to executive‑level presentations
  • Mentor junior consultants and senior consultants, and review their technical work
  • Ensure solutions align with governance, security, and responsible AI standards (as applicable)

  Requirements

  • Must be able to OBTAIN and MAINTAIN a Federal or DHS "PUBLIC TRUST"; candidates must obtain approved adjudication of their PUBLIC TRUST prior to onboarding with Guidehouse. Candidates with an ACTIVE PUBLIC TRUST or SUITABILITY are preferred
  • Bachelor’s degree
  • EIGHT (8) or more years of experience in AI, data science, analytics, or engineering
  • FOUR (4) or more years of experience in a fraud/payment integrity-related role
  • Experience in Python/R, SQL, and data modeling
  • Experience with statistical and data analytics
  • Experience working with various data structure formats (CSV/TXT, JSON, XML, Parquet, etc.)
  • Experience developing, testing, and validating machine learning and other AI models at scale
  • Experience with data visualization tools (PowerBI, Tableau, Looker, etc.)
  • Experience with applying data analytics and artificial intelligence in the financial crime compliance and/or fraud, waste, and abuse prevention space
  • Travel will be 25-50% for candidates not located in the DMV or NYC area

  Qualifications

  • Experience leading small teams of junior resources
  • Proven ability to communicate complex concepts to non‑technical audiences
  • Experience owning deliverable workstreams
  • Experience building fraud and/or fincrime monitoring rules in one or more programming languages
  • Experience working for or supporting healthcare technology, healthcare business or healthcare process initiatives
  • Cloud