Overview In this role you translate complex business problems into structured decision models and quantify tradeoffs to improve decision quality at scale. You will collaborate with business leaders and technical partners to define decision requirements, logic, and measurable outcomes, while operating in regulated environments. The position starts on-site in Lansing with remote flexibility after training, offering impact across financial, operational, or risk outcomes. You'll apply structured methods (DMN, decision trees, optimization, cost-benefit) and leverage SQL and Python to deliver actionable insights. ResponsibilitiesDecompose complex processes into explicit decision points and decision flowsDefine decision logic, inputs, outputs, constraints, and measurable outcomesModel decisions using structured methods (e.g., DMN, decision trees, optimization framing)Quantify tradeoffs, thresholds, and risk tolerancesPartner with business leaders to define decision requirements and communicate analytical findings in operational termsInfluence process changes based on evidence and structured resultsDocument decision logic in auditable, reproducible mannerOperate in regulated or compliance-sensitive environments Key requirementsStrong decision modeling & structuringQuantitative & analytical expertise (SQL, Python)Experience with sensitivity/scenario/cost-benefit analysesBusiness translation and stakeholder leadershipGovernance, risk awareness, and auditable documentationStakeholder managementClear communication of analytical findingsAbility to influence process changesSQL proficiencyPython for advanced analyticsDMN and structured decision modeling
Not specified in the original listing.
Not specified in the original listing.
