Sr. Analyst, Statistical Forecast & Accuracy
for section headings like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We should only include sections that have real specific content. The posting includes a Position Summary (maybe About the role). It includes Key Responsibilities. It includes Minimum Requirement (maybe Requirements). It includes Education (maybe Qualifications). It includes Critical Skills (Skills). It includes Additional Skills (maybe also Skills). It includes Compensation Range (Pay). It includes hybrid schedule details (Schedule). Benefits: there is a line "We are proud to offer a competitive compensation package at McKesson as part of our Total Rewards. This is determined by several factors... In addition to base pay, other compensation, such as an annual bonus or long-term incentive opportunities may be offered. For more information regarding benefits at McKesson, please click here." That's vague, not specific benefits. No concrete benefits listed. So we should not create Benefits section because no specific content. Also we have Physical Requirements (Traditional office requirements...). That could be part of Requirements? But we can include maybe a separate section? The instruction says use headings for those specific categories; we can include a section only if posting has real specific content. Physical Requirements is specific: "Traditional office requirements. A large percentage of time performing computer-based work is required.Hybrid role, must live near Las Colinas office.Up to 5% travel." That's schedule/location info; maybe part of Schedule? Actually schedule includes hybrid days, travel. We can incorporate that into Schedule section. So we will have sections: About the role (Position Summary), Responsibilities (Key Responsibilities), Requirements (Minimum Requirement), Qualifications (Education), Skills (Critical Skills + Additional Skills maybe combined), Pay (Compensation Range), Schedule (Hybrid role details, travel). We must not repeat job title as heading. Also no Job ID etc.
We need to use - for any list of duties/requirements/benefits, and
for prose. So for responsibilities we should list each bullet as
- . The responsibilities are described in paragraphs; we can break them into bullet points. We need to preserve all substantive information; not invent or summarize away detail. So we need to capture each responsibility point.
Let's extract responsibilities:
From "Key Responsibilities Statistical Forecasting & Model Governance Own the configuration and maintenance of statistical forecast parameters in Kinaxis Maestro, including model selection and parameter tuning. Apply history cleansing disciplines prior to each forecast cycle, adjusting for outliers, customer losses, NDC switches, and new product launches to ensure the statistical baseline reflects true underlying demand patterns. Intervene directly when the system produces outputs that are wrong: update model parameters, alter model selection, and document the rationale for every change so that interventions are traceable and auditable. Serve as the primary point of contact for the COE on statistical forecast configuration, parameter governance, and planning engine integrity questions."
Then "Forecast Accuracy & Bias Management Own the forecast accuracy and bias measurement framework across all portfolios, tracking MAPE, bias, and error metrics at the appropriate level of granularity to surface actionable insights rather than just headline numbers. Conduct structured root cause analysis on forecast misses, distinguishing between model failure, enrichment failure, and genuine demand variability, and communicating findings clearly to the Consensus Demand Planning Lead and Channel Leads. Identify and flag systematic bias in the statistical forecast, whether directional over- or under-forecasting by product type, channel, or time horizon, and drive model adjustments to correct it. Maintain a continuous improvement cadence, tracking accuracy trend over time and holding the team accountable to improving against a defined baseline as the system matures and data quality improves. Partner with Channel Leads to determine whether a forecast miss originated in the statistical baseline or in enrichment inputs, and prepare forecast performance reporting for S&OP reviews facilitated by the COE, ensuring accuracy findings are visible to cross-functional participants and tied to operational implications for supply and inventory."
We can split into two sub-sections? But we only have one Responsibilities heading; we can keep paragraphs or list items. Probably better to make each bullet a responsibility.
Let's create list items:
- Own the configuration and maintenance of statistical forecast parameters in Kinaxis Maestro, including model selection and parameter tuning.
- Apply history cleansing disciplines prior to each forecast cycle, adjusting for outliers, customer losses, NDC switches, and new product launches to ensure the statistical baseline reflects true underlying demand patterns.
- Intervene directly when the system produces outputs that are wrong: update model parameters, alter model selection, and document the rationale for every change so that interventions are traceable and auditable.
- Serve as the primary point of contact for the COE on statistical forecast configuration, parameter governance, and planning engine integrity questions.
- Own the forecast accuracy and bias measurement framework across all portfolios, tracking MAPE, bias, and error metrics at the appropriate level of granularity to surface actionable insights rather than just headline numbers.
- Conduct structured root cause analysis on forecast misses, distinguishing between model failure, enrichment failure, and genuine demand variability, and communicating findings clearly to the Consensus Demand Planning Lead and Channel Leads.
- Identify and flag systematic bias in the statistical forecast, whether directional over- or under-forecasting by product type, channel, or time horizon, and drive model adjustments to correct it.
- Maintain a continuous improvement cadence, tracking accuracy trend over time and holding the team accountable to improving against a defined baseline as the system matures and data quality improves.
- Partner with Channel Leads to determine whether a forecast miss originated in the statistical baseline or in enrichment inputs, and prepare forecast performance reporting for S&OP reviews facilitated by the COE, ensuring accuracy findings are visible to cross-functional participants and tied to operational implications for supply and inventory.
Now Requirements: "Minimum Requirement Degree or equivalent and typically requires 7+ years of relevant experience." That's a sentence. Also maybe "Education Bachelor's degree in Supply Chain, Statistics, Data Science, Mathematics, or a related quantitative field strongly preferred or equivalent experience." That's under Education but we have separate Qualifications section. So Requirements could be the degree/experience line. We'll put as
.
Qualifications: Education bullet: "Bachelor's degree in Supply Chain, Statistics, Data Science, Mathematics, or a related quantitative field strongly preferred or equivalent experience." Could be a
or
. Since it's a single line, we can use .
Skills: Critical Skills list (multiple bullet points). Also Additional Skills list. We'll combine into one Skills section with list items.
Let's extract Critical Skills bullet points (they are sentences separated by periods). Let's list:
- 7+ years in demand planning, supply chain analytics, or a related field, with demonstrated hands-on experience owning statistical forecast configuration and model governance in a production planning environment.
- Direct experience working in Kinaxis Maestro, including parameter configuration, model selection, and demand planning engine operation.
- Experience in a comparable advanced planning system (SAP IBP, Blue Yonder, o9) considered with a clear expectation of rapid Maestro proficiency.
- Demonstrated ability to diagnose and correct statistical forecast failures, including history cleansing, outlier management, and model parameter adjustment.
- Proven ability to build and maintain a forecast accuracy and bias measurement framework, including root cause analysis and continuous improvement tracking.
- Configuring, maintaining, and intervening in Kinaxis Maestro to ensure the statistical forecast engine produces reliable outputs across all portfolios.
- Applying disciplined cleansing and data preparation so that the statistical baseline reflects real demand patterns rather than data noise.
- Diagnosing forecast failures with precision, distinguishing model problems from enrichment problems from genuine demand variability, and routing accountability correctly.
- Building and sustaining a bias management discipline that improves forecast quality over time rather than accepting persistent error as unavoidable.
- Operating as the technical anchor for a team that is otherwise oriented toward commercial and market judgment, without creating a bottleneck or a knowledge silo.
Additional Skills:
- Experience operating within a structured S&OP or consensus planning process, including preparing performance reporting for cross-functional review.
- Familiarity with pharmaceutical, healthcare, or wholesale distribution demand dynamics is a strong plus, particularly experience with product lifecycle events, NDC switches, and new business onboarding that create history anomalies.
- Comfort operating in ambiguity and building process structure where governance is still maturing, particularly in the context of a large-scale system transition where baselines and benchmarks do not yet exist.
- Ability to communicate technical findings clearly to non-technical stakeholders, including explaining why the system produced a wrong output and what was done to fix it.
We'll combine these into a single
list.
Pay: "Compensation Range $104,000-138,600-173,300 with 15% MIPs bonus eligibility." Also maybe mention "This role is a hybrid position..." but that's schedule. We'll put Pay as with that sentence.
Schedule: "This role is a hybrid position. The selected candidate is expected to work on-site at our Las Colinas office a minimum of two (2) days per week, with the remaining days worked remotely. Specific in-office days may be designated based on team needs and business priorities." Also from Physical Requirements: "Hybrid role, must live near Las Colinas office. Up to 5% travel." Combine.
We'll create Schedule section with
containing that info.
About the role: Position Summary paragraph(s). Let's extract:
"McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve – we care. What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow’s health today, we want to hear from you. Position Summary The Sr. Analyst, Statistical Forecast & Accuracy is an individual contributor within the Demand Planning team, reporting directly to the Consensus Demand Planning Lead. This role is the technical authority for the statistical forecast that underlies the consensus plan. The Sr. Analyst is accountable for ensuring the system produces a reliable, accurate baseline forecast across portfolios, and governing forecast performance over time. This role intervenes when the engine produces outputs that do not reflect reality, manages model parameters and bias across portfolios, and drives the continuous improvement discipline that makes the consensus forecast credible and defensible. This is a technical role that requires deep proficiency in statistical forecasting methods, hands-on expertise in Kinaxis Maestro, and the judgment to distinguish a model problem from a demand reality problem. The Sr. Analyst must be able to translate statistical findings into clear, actionable guidance for the Consensus Demand Planning Lead."
We'll put that as
under About the role heading.
Now ensure we don't include boilerplate like EEO, scam warning, etc.
Now produce HTML fragment:
About the role
...
Responsibilities
- ...
...
Requirements
Degree or equivalent and typically requires 7+ years of relevant experience.
Qualifications
Bachelor's degree in Supply Chain, Statistics, Data Science, Mathematics, or a related quantitative field strongly preferred or equivalent experience.
Skills
- ... (all skills)
...
Pay
Compensation Range $104,000-138,600-173,300 with 15% MIPs bonus eligibility.
Schedule
This role is a hybrid position. The selected candidate is expected to work on-site at our Las Colinas office a minimum of two (2) days per week, with the remaining days worked remotely. Specific in-office days may be designated based on team needs and business priorities. Hybrid
for prose. So for responsibilities we should list each bullet as
. Qualifications: Education bullet: "Bachelor's degree in Supply Chain, Statistics, Data Science, Mathematics, or a related quantitative field strongly preferred or equivalent experience." Could be a
or
- . Since it's a single line, we can use
- ... ...
- ... (all skills) ...
. Skills: Critical Skills list (multiple bullet points). Also Additional Skills list. We'll combine into one Skills section with list items. Let's extract Critical Skills bullet points (they are sentences separated by periods). Let's list: - 7+ years in demand planning, supply chain analytics, or a related field, with demonstrated hands-on experience owning statistical forecast configuration and model governance in a production planning environment. - Direct experience working in Kinaxis Maestro, including parameter configuration, model selection, and demand planning engine operation. - Experience in a comparable advanced planning system (SAP IBP, Blue Yonder, o9) considered with a clear expectation of rapid Maestro proficiency. - Demonstrated ability to diagnose and correct statistical forecast failures, including history cleansing, outlier management, and model parameter adjustment. - Proven ability to build and maintain a forecast accuracy and bias measurement framework, including root cause analysis and continuous improvement tracking. - Configuring, maintaining, and intervening in Kinaxis Maestro to ensure the statistical forecast engine produces reliable outputs across all portfolios. - Applying disciplined cleansing and data preparation so that the statistical baseline reflects real demand patterns rather than data noise. - Diagnosing forecast failures with precision, distinguishing model problems from enrichment problems from genuine demand variability, and routing accountability correctly. - Building and sustaining a bias management discipline that improves forecast quality over time rather than accepting persistent error as unavoidable. - Operating as the technical anchor for a team that is otherwise oriented toward commercial and market judgment, without creating a bottleneck or a knowledge silo. Additional Skills: - Experience operating within a structured S&OP or consensus planning process, including preparing performance reporting for cross-functional review. - Familiarity with pharmaceutical, healthcare, or wholesale distribution demand dynamics is a strong plus, particularly experience with product lifecycle events, NDC switches, and new business onboarding that create history anomalies. - Comfort operating in ambiguity and building process structure where governance is still maturing, particularly in the context of a large-scale system transition where baselines and benchmarks do not yet exist. - Ability to communicate technical findings clearly to non-technical stakeholders, including explaining why the system produced a wrong output and what was done to fix it. We'll combine these into a single
- list.
Pay: "Compensation Range $104,000-138,600-173,300 with 15% MIPs bonus eligibility." Also maybe mention "This role is a hybrid position..." but that's schedule. We'll put Pay as
with that sentence. Schedule: "This role is a hybrid position. The selected candidate is expected to work on-site at our Las Colinas office a minimum of two (2) days per week, with the remaining days worked remotely. Specific in-office days may be designated based on team needs and business priorities." Also from Physical Requirements: "Hybrid role, must live near Las Colinas office. Up to 5% travel." Combine. We'll create Schedule section with
containing that info. About the role: Position Summary paragraph(s). Let's extract: "McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve – we care. What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow’s health today, we want to hear from you. Position Summary The Sr. Analyst, Statistical Forecast & Accuracy is an individual contributor within the Demand Planning team, reporting directly to the Consensus Demand Planning Lead. This role is the technical authority for the statistical forecast that underlies the consensus plan. The Sr. Analyst is accountable for ensuring the system produces a reliable, accurate baseline forecast across portfolios, and governing forecast performance over time. This role intervenes when the engine produces outputs that do not reflect reality, manages model parameters and bias across portfolios, and drives the continuous improvement discipline that makes the consensus forecast credible and defensible. This is a technical role that requires deep proficiency in statistical forecasting methods, hands-on expertise in Kinaxis Maestro, and the judgment to distinguish a model problem from a demand reality problem. The Sr. Analyst must be able to translate statistical findings into clear, actionable guidance for the Consensus Demand Planning Lead." We'll put that as
under About the role heading. Now ensure we don't include boilerplate like EEO, scam warning, etc. Now produce HTML fragment:
About the role
...
Responsibilities
Requirements
Degree or equivalent and typically requires 7+ years of relevant experience.
Qualifications
Bachelor's degree in Supply Chain, Statistics, Data Science, Mathematics, or a related quantitative field strongly preferred or equivalent experience.
Skills
Pay
Compensation Range $104,000-138,600-173,300 with 15% MIPs bonus eligibility.
Schedule
This role is a hybrid position. The selected candidate is expected to work on-site at our Las Colinas office a minimum of two (2) days per week, with the remaining days worked remotely. Specific in-office days may be designated based on team needs and business priorities. Hybrid