What are the responsibilities and job description for the Supply Chain Analytics Manager position at TADA?
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Information, Please See
https://illinoisjoblink.illinois.gov/jobs/13423834
**Supply Chain Analytics Manager**
Lead operations research and decision science initiatives to optimize
supply chain planning and execution, focusing on demandsupply
visibility, inventory positioning, constrained allocation, and capacity
bottleneck mitigation. Partner with global stakeholders to translate
complex planning needs into quantitative decision models, governed
performance measures, and repeatable decision workflows aligned to
execution reviews and S&OP cadences.
**Key Responsibilities**
for demand supply balancing, constrained resource allocation, and
service-level protection.
segmentation-based logic and optimization techniques, such as network
flow and heuristic approaches where appropriate.
uncertainty and supply disruptions. Perform sensitivity analysis and
stress testing to quantify impacts on service levels, inventory
performance, and fulfillment risk.
source-to-target mappings and implement automated data quality controls,
including reconciliation, anomaly detection, and KPI validation.
outputs and exceptions to ensure alignment with ERP/MRP planning signals
and business cadence.
cross-functional adoption of model-driven workflows, and delivering
executive-ready summaries to global stakeholder groups.
**Minimum Requirements**
a related quantitative field.
translate planning needs into quantitative models and decision-ready
recommendations.
Developing models for inventory policy tradeoffs, constrained
allocation, and capacity mitigation within ERP/MRP-driven environments.
Building and governing model-ready datasets in cloud platforms (e.g.,
Snowflake/Databricks) using SQL, including data validation and quality
controls.
Designing and executing scenario analysis, sensitivity testing, and
back-testing to validate model robustness and quantify uncertainty.
Leading and mentoring analysts in model development, validation, and
documentation standards.
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Supply Chain Analytics Manager
Lead operations research and decision science initiatives to optimize
supply chain
planning and execution, focusing on demandsupply visibility, inventory
positioning,
constrained allocation, and capacity bottleneck mitigation. Partner with
global
stakeholders to translate complex planning needs into quantitative
decision models,
governed performance measures, and repeatable decision workflows aligned
to execution
reviews and S&OP cadences.
Key Responsibilities
goals, decision variables, constraints, and objective functions for
demand supply
balancing, constrained resource allocation, and service-level
protection.
inventory prioritization and constrained part allocation using
segmentation-based
logic and optimization techniques, such as network flow and heuristic
approaches
where appropriate.
style what-if simulation to evaluate tradeoffs under demand uncertainty
and supply
disruptions. Perform sensitivity analysis and stress testing to quantify
impacts on
service levels, inventory performance, and fulfillment risk.
as Snowflake, using SQL transformations. Define source-to-target
mappings and
implement automated data quality controls, including reconciliation,
anomaly
detection,
Information, Please See
https://illinoisjoblink.illinois.gov/jobs/13423834
**Supply Chain Analytics Manager**
Lead operations research and decision science initiatives to optimize
supply chain planning and execution, focusing on demandsupply
visibility, inventory positioning, constrained allocation, and capacity
bottleneck mitigation. Partner with global stakeholders to translate
complex planning needs into quantitative decision models, governed
performance measures, and repeatable decision workflows aligned to
execution reviews and S&OP cadences.
**Key Responsibilities**
- Problem Formulation:** Define complex decision problems by identifying
for demand supply balancing, constrained resource allocation, and
service-level protection.
- Model Development:** Develop and implement analytical decision models
segmentation-based logic and optimization techniques, such as network
flow and heuristic approaches where appropriate.
- Simulation & Analysis:** Design scenario analysis frameworks using
uncertainty and supply disruptions. Perform sensitivity analysis and
stress testing to quantify impacts on service levels, inventory
performance, and fulfillment risk.
- Data Foundations:** Architect model-ready datasets in cloud data
source-to-target mappings and implement automated data quality controls,
including reconciliation, anomaly detection, and KPI validation.
- Operationalization:** Automate recurring model runs and decision
outputs and exceptions to ensure alignment with ERP/MRP planning signals
and business cadence.
- Leadership:** Provide technical leadership by mentoring analysts,
cross-functional adoption of model-driven workflows, and delivering
executive-ready summaries to global stakeholder groups.
**Minimum Requirements**
- Education:** Masters degree in Computer Science (Data/Analytics),
a related quantitative field.
- Experience:** At least 1 year of experience in the following:
translate planning needs into quantitative models and decision-ready
recommendations.
Developing models for inventory policy tradeoffs, constrained
allocation, and capacity mitigation within ERP/MRP-driven environments.
Building and governing model-ready datasets in cloud platforms (e.g.,
Snowflake/Databricks) using SQL, including data validation and quality
controls.
Designing and executing scenario analysis, sensitivity testing, and
back-testing to validate model robustness and quantify uncertainty.
Leading and mentoring analysts in model development, validation, and
documentation standards.
::: {#/docProps/thumbnail.emf}
:::
Supply Chain Analytics Manager
Lead operations research and decision science initiatives to optimize
supply chain
planning and execution, focusing on demandsupply visibility, inventory
positioning,
constrained allocation, and capacity bottleneck mitigation. Partner with
global
stakeholders to translate complex planning needs into quantitative
decision models,
governed performance measures, and repeatable decision workflows aligned
to execution
reviews and S&OP cadences.
Key Responsibilities
- Problem Formulation: Define complex decision problems by identifying
goals, decision variables, constraints, and objective functions for
demand supply
balancing, constrained resource allocation, and service-level
protection.
- Model Development: Develop and implement analytical decision models
inventory prioritization and constrained part allocation using
segmentation-based
logic and optimization techniques, such as network flow and heuristic
approaches
where appropriate.
- Simulation & Analysis: Design scenario analysis frameworks using
style what-if simulation to evaluate tradeoffs under demand uncertainty
and supply
disruptions. Perform sensitivity analysis and stress testing to quantify
impacts on
service levels, inventory performance, and fulfillment risk.
- Data Foundations: Architect model-ready datasets in cloud data
as Snowflake, using SQL transformations. Define source-to-target
mappings and
implement automated data quality controls, including reconciliation,
anomaly
detection,