Senior Forecasting & Business Analytics Consultant (AI) (Indianapolis)

IWU is seeking a Senior Forecasting & Business Analytics Consultant (AI) (Independent Contractor ‑ 1099 / Contract-to-Hire) for a large-scale technology reorganization project.

ABOUT IWU TECHNOLOGY

ABOUT THE ROLE:

• IWU is re-platforming its enterprise on a multi-data center, AI-first data foundation with a dedicated analytics planning, design, and build track on the roadmap. We need reporting that executives trust and forecasts that hold up under scrutiny. We are seeking a Senior Forecasting & Business Analytics Consultant with strong hands-on forecasting and actuarial modeling skills to lead IWU's forward-looking analytics functions.
• This is not a dashboard-only role. You will run a small analytics team , and the enterprise reporting portfolio, and stay hands-on in the models – cohort retention, tuition and aid scenarios, headcount and capacity forecasts, and multi-year financial projections that Finance, Leadership, and the CIO rely on.
• You will partner across IT, Institutional Research, Finance, and academic operations while standing up analytics capabilities on our on-premises data platform .
• You will be a people leader who still opens the spreadsheet, SQL editor, Python, or modeling tool when the forecast matters – you set standards for the team, quality-check the math, and explain variance to leadership in plain language.

Reporting and Analytics Program Leadership

• Drive the forward-looking analytics portfolio – executive dashboards, operational reports, self-service datasets, and KPI definitions aligned to IWU's strategic and re-platforming priorities.
• Develop the analytics workstream through planning, design, and build phases – requirements, data sourcing, semantic models, report catalog, and release governance per the re-platforming roadmap.
• Define reporting standards – naming, refresh cadence, data lineage documentation, access controls, and change management so reports do not become conflicting sources of truth.

Forecasting and Actuarial Modeling (Hands-On)

• Develop and maintain enrollment and retention forecasts – cohort models, persistence curves, channel mix (online vs on-campus, graduate vs undergraduate), and scenario analysis leadership uses for planning.
• Build revenue and tuition forecasting models – net tuition, financial aid impact, discount rates, and program-level projections with documented assumptions and sensitivity analysis.
• Apply advanced statistical and forecasting methods – survival analysis for retention and persistence, cohort-based attrition modeling, confidence intervals, Monte Carlo simulations, scenario trees, and back-testing against actual enrollment, completion, and financial outcomes.
• Own the forecast cadence – monthly actuals vs forecast variance analysis, re-baseline triggers, and executive-ready narrative on what changed and why.

Data Foundation and Analytics Delivery

• Partner with Data Platform and DBA teams on our Single-Source-of-Truth and Data Warehouse – source integration, dimensional models, metric layers, and vector/analytics adjacency for AI-enabled reporting where standards apply.
• Design trusted datasets and semantic models – single definitions for headcount, enrollment, completion, revenue, and operational KPIs used across reports and forecasts.
• Implement data quality checks on reporting inputs – reconciliation to systems of record, anomaly detection, and escalation when source data breaks forecasts or dashboards.
• Align analytics delivery with identity and security standards – row-level security, FERPA-appropriate access, and audit trails for sensitive institutional data.

Stakeholder Partnership and Governance

• Partner with Finance, Institutional Research, enrollment management, and academic leaders – translate their questions into models and reports they will actually use in decisions.
• Present forecast results and uncertainty honestly – ranges, assumptions, and risks – not false precision that collapses at the first bad semester.
• Support audit, accreditation, and compliance reporting – Title IV, FERPA, board materials, and SOX-adjacent controls where IT spend and headcount evidence is required.
• Document methodology and model governance – version control, assumption logs, approval workflows, and reproducibility so forecasts survive leadership transitions.

WHAT WE ARE LOOKING FOR:

Required

• According to Indiana Wesleyan University policy, all employees and contract-to-hire contractors must possess a strong Christian commitment and adhere to the standards outlined in the IWU Community Lifestyle Statement .
• 8+ years of progressive experience in business intelligence, institutional analytics, financial analysis, or actuarial science, with 3+ years in a people-management or team-lead capacity.
• Demonstrated hands-on forecasting experience – you personally build and maintain models, not only delegate them – with track record of forecasts reviewed by Finance or executive leadership.
• Actuarial or advanced statistical modeling skills – cohort/survival methods, regression, time series, scenario modeling, or equivalent techniques applied to enrollment, retention, or financial outcomes.
• Strong SQL and analytics tool proficiency – complex queries, data modeling, and production reporting in Python, Power BI, Tableau, or equivalent enterprise BI platforms.
• Experience delivering executive and board-ready reporting – clear visuals, accurate numbers, and narrative that non-technical leaders can act on.
• Financial acumen – tuition revenue, aid, budgets, variance analysis, and multi-year planning vocabulary comfortable in higher-ed or similarly complex institutions.
• Bachelor's degree in Actuarial Science, Statistics, Finance, Economics, Information Systems, or a related field – or equivalent demonstrated experience .

Strongly Preferred

• Higher-education , non-profit, or other mission-driven institutional experience – enrollment management, registrar, or institutional research collaboration.
• Experience with Python or R for forecasting, statistical modeling, and reproducible analytics pipelines .
• Familiarity with SQL Server, data lake/warehouse design, and on-premises analytics platforms – not analytics exclusively in SaaS warehouses.
• Experience supporting Title IV, IPEDS, accreditation, or board reporting in a university context .
• Knowledge of FERPA and data governance for student and financial analytics.
• Background in ERP/student system analytics – Colleague or similar – and migration reporting during re-platforming.
• Experience integrating AI-assisted analytics – natural-language query, embedded insights, or ML forecasts – within governance and data-classification standards.
• Relevant certifications (Microsoft Power BI, Tableau, FMVA, or equivalent demonstrated depth).

How You Work

• You trust but verify the data – a beautiful chart on bad joins is worse than no chart at all.
• You show assumptions and uncertainty – actuarial discipline means leadership knows what the model depends on.
• You stay hands-on – managers who cannot debug a model lose the team when variance hits.
• You translate quantitative results for humans – enrollment deans and CIOs should not need a statistics degree to use your output.

WHY THIS ROLE?

• Dual mandate: lead and model . You build the analytics function and personally own the forecasts that matter – rare combination with real institutional impact.
• Higher-ed complexity done right . Online/campus mix, graduate/undergraduate split, aid, and mission-driven growth – the modeling is genuinely interesting, not generic SaaS metrics.
• Executive visibility . Enrollment and revenue forecasts reach leadership and the board – your work informs real decisions about IWU's future.
• Mission and meaning . IWU is a century-old Christ-centered university. The forecasts and reports you deliver help stew resources wisely in service of roughly 15,000 learners.

PROJECT REMUNERATION:

Estimated annual project remuneration is $155,000 - $185,000 for this independent contractor (1099) / Contract-to-Hire role.

Contractor Insurance/Bond Requirements

• General Liability: $1m per occurrence / $2m aggregate
• Cyber Liability: $2m per occurrence
• Workers’ Compensation / Employers’ Liability: $500,000; not applicable for approved sole operators
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