Goal templates — Data Science — P7

Data Science & Analytics · Data Science · P7 — Staff / Distinguished Professional

These are canon-derived frames, not advice: every line is either verbatim JobFrame canon text or a fixed template wrapping it. ⟨target⟩ / ⟨baseline⟩ / ⟨date⟩ are placeholders for the manager to fill in. Nothing here is generated by AI — rows are omitted, never invented, when the canon lacks the underlying field.

SMART goals

One row per canon core output / responsibility this level owns.

JFM responsibility (P7)

Sets direction for the data science function and anticipates emerging challenges, defining long-term AI/ML roadmaps that influence company-wide strategy and industry practice.

Specific: Deliver: "Sets direction for the data science function and anticipates emerging challenges, defining long-term AI/ML roadmaps that influence company-wide strategy and industry practice."
Measurable: Move the metric this drives from ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩.
Achievable: Scoped to this level's jfm complexity/problem-solving rubric: "Solves precedent-free, ambiguous problems with broad business and industry consequences; anticipates emerging challenges."
Relevant: Advances the Data Science & Analytics · Data Science mandate for a P7 — Staff / Distinguished Professional.
Time-bound: ⟨date⟩

JFM responsibility (P7)

Solves precedent-free, ambiguous problems and develops new models, methods, or technologies with broad business and industry consequences.

Specific: Deliver: "Solves precedent-free, ambiguous problems and develops new models, methods, or technologies with broad business and industry consequences."
Measurable: Move the metric this drives from ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩.
Achievable: Scoped to this level's jfm complexity/problem-solving rubric: "Solves precedent-free, ambiguous problems with broad business and industry consequences; anticipates emerging challenges."
Relevant: Advances the Data Science & Analytics · Data Science mandate for a P7 — Staff / Distinguished Professional.
Time-bound: ⟨date⟩

JFM responsibility (P7)

Networks with executives, boards, regulators, and industry leaders, persuading and educating senior stakeholders on strategic data and AI priorities.

Specific: Deliver: "Networks with executives, boards, regulators, and industry leaders, persuading and educating senior stakeholders on strategic data and AI priorities."
Measurable: Move the metric this drives from ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩.
Achievable: Scoped to this level's jfm complexity/problem-solving rubric: "Solves precedent-free, ambiguous problems with broad business and industry consequences; anticipates emerging challenges."
Relevant: Advances the Data Science & Analytics · Data Science mandate for a P7 — Staff / Distinguished Professional.
Time-bound: ⟨date⟩

JFM responsibility (P7)

Provides high-level mentorship to senior and principal data scientists, shaping company-wide technical capability without direct reports.

Specific: Deliver: "Provides high-level mentorship to senior and principal data scientists, shaping company-wide technical capability without direct reports."
Measurable: Move the metric this drives from ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩.
Achievable: Scoped to this level's jfm complexity/problem-solving rubric: "Solves precedent-free, ambiguous problems with broad business and industry consequences; anticipates emerging challenges."
Relevant: Advances the Data Science & Analytics · Data Science mandate for a P7 — Staff / Distinguished Professional.
Time-bound: ⟨date⟩

JFM responsibility (P7)

Operates with complete independence, establishing the governance, ethics, and risk frameworks that define how AI systems are built and deployed.

Specific: Deliver: "Operates with complete independence, establishing the governance, ethics, and risk frameworks that define how AI systems are built and deployed."
Measurable: Move the metric this drives from ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩.
Achievable: Scoped to this level's jfm complexity/problem-solving rubric: "Solves precedent-free, ambiguous problems with broad business and industry consequences; anticipates emerging challenges."
Relevant: Advances the Data Science & Analytics · Data Science mandate for a P7 — Staff / Distinguished Professional.
Time-bound: ⟨date⟩

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1. Sets direction for the data science function and anticipates emerging challenges, defining long-term AI/ML roadmaps that influence company-wide strategy and industry practice.  [source: JFM responsibility (P7)]
   Specific:    Deliver: "Sets direction for the data science function and anticipates emerging challenges, defining long-term AI/ML roadmaps that influence company-wide strategy and industry practice."
   Measurable:  Move the metric this drives from ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩.
   Achievable:  Scoped to this level's jfm complexity/problem-solving rubric: "Solves precedent-free, ambiguous problems with broad business and industry consequences; anticipates emerging challenges."
   Relevant:    Advances the Data Science & Analytics · Data Science mandate for a P7 — Staff / Distinguished Professional.
   Time-bound:  ⟨date⟩

2. Solves precedent-free, ambiguous problems and develops new models, methods, or technologies with broad business and industry consequences.  [source: JFM responsibility (P7)]
   Specific:    Deliver: "Solves precedent-free, ambiguous problems and develops new models, methods, or technologies with broad business and industry consequences."
   Measurable:  Move the metric this drives from ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩.
   Achievable:  Scoped to this level's jfm complexity/problem-solving rubric: "Solves precedent-free, ambiguous problems with broad business and industry consequences; anticipates emerging challenges."
   Relevant:    Advances the Data Science & Analytics · Data Science mandate for a P7 — Staff / Distinguished Professional.
   Time-bound:  ⟨date⟩

3. Networks with executives, boards, regulators, and industry leaders, persuading and educating senior stakeholders on strategic data and AI priorities.  [source: JFM responsibility (P7)]
   Specific:    Deliver: "Networks with executives, boards, regulators, and industry leaders, persuading and educating senior stakeholders on strategic data and AI priorities."
   Measurable:  Move the metric this drives from ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩.
   Achievable:  Scoped to this level's jfm complexity/problem-solving rubric: "Solves precedent-free, ambiguous problems with broad business and industry consequences; anticipates emerging challenges."
   Relevant:    Advances the Data Science & Analytics · Data Science mandate for a P7 — Staff / Distinguished Professional.
   Time-bound:  ⟨date⟩

4. Provides high-level mentorship to senior and principal data scientists, shaping company-wide technical capability without direct reports.  [source: JFM responsibility (P7)]
   Specific:    Deliver: "Provides high-level mentorship to senior and principal data scientists, shaping company-wide technical capability without direct reports."
   Measurable:  Move the metric this drives from ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩.
   Achievable:  Scoped to this level's jfm complexity/problem-solving rubric: "Solves precedent-free, ambiguous problems with broad business and industry consequences; anticipates emerging challenges."
   Relevant:    Advances the Data Science & Analytics · Data Science mandate for a P7 — Staff / Distinguished Professional.
   Time-bound:  ⟨date⟩

5. Operates with complete independence, establishing the governance, ethics, and risk frameworks that define how AI systems are built and deployed.  [source: JFM responsibility (P7)]
   Specific:    Deliver: "Operates with complete independence, establishing the governance, ethics, and risk frameworks that define how AI systems are built and deployed."
   Measurable:  Move the metric this drives from ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩.
   Achievable:  Scoped to this level's jfm complexity/problem-solving rubric: "Solves precedent-free, ambiguous problems with broad business and industry consequences; anticipates emerging challenges."
   Relevant:    Advances the Data Science & Analytics · Data Science mandate for a P7 — Staff / Distinguished Professional.
   Time-bound:  ⟨date⟩

OKRs

Objectives from this level's core outputs; key results only where a real dimension or capability backs them.

JFM responsibility (P7)

Sets direction for the data science function and anticipates emerging challenges, defining long-term AI/ML roadmaps that influence company-wide strategy and industry practice.

From ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩ — tied to: "Sets direction for the data science function and anticipates emerging challenges, defining long-term AI/ML roadmaps that influence company-wide strategy and industry practice."
Evidence at this level's scope bar: "Cross-organization / enterprise technical strategy" — ⟨target⟩ by ⟨date⟩

JFM responsibility (P7)

Solves precedent-free, ambiguous problems and develops new models, methods, or technologies with broad business and industry consequences.

From ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩ — tied to: "Solves precedent-free, ambiguous problems and develops new models, methods, or technologies with broad business and industry consequences."
Evidence at this level's autonomy bar: "Operates autonomously at the enterprise level" — ⟨target⟩ by ⟨date⟩

JFM responsibility (P7)

Networks with executives, boards, regulators, and industry leaders, persuading and educating senior stakeholders on strategic data and AI priorities.

From ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩ — tied to: "Networks with executives, boards, regulators, and industry leaders, persuading and educating senior stakeholders on strategic data and AI priorities."
Evidence at this level's complexity bar: "Industry-level, highly ambiguous problems" — ⟨target⟩ by ⟨date⟩

JFM responsibility (P7)

Provides high-level mentorship to senior and principal data scientists, shaping company-wide technical capability without direct reports.

From ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩ — tied to: "Provides high-level mentorship to senior and principal data scientists, shaping company-wide technical capability without direct reports."
Evidence at this level's impact bar: "Enterprise-wide" — ⟨target⟩ by ⟨date⟩

JFM responsibility (P7)

Operates with complete independence, establishing the governance, ethics, and risk frameworks that define how AI systems are built and deployed.

From ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩ — tied to: "Operates with complete independence, establishing the governance, ethics, and risk frameworks that define how AI systems are built and deployed."
Evidence at this level's decision rights bar: "Final technical authority across multiple domains" — ⟨target⟩ by ⟨date⟩

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Objective 1: Sets direction for the data science function and anticipates emerging challenges, defining long-term AI/ML roadmaps that influence company-wide strategy and industry practice. [source: JFM responsibility (P7)]
KR1. From ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩ — tied to: "Sets direction for the data science function and anticipates emerging challenges, defining long-term AI/ML roadmaps that influence company-wide strategy and industry practice."
KR2. Evidence at this level's scope bar: "Cross-organization / enterprise technical strategy" — ⟨target⟩ by ⟨date⟩

Objective 2: Solves precedent-free, ambiguous problems and develops new models, methods, or technologies with broad business and industry consequences. [source: JFM responsibility (P7)]
KR1. From ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩ — tied to: "Solves precedent-free, ambiguous problems and develops new models, methods, or technologies with broad business and industry consequences."
KR2. Evidence at this level's autonomy bar: "Operates autonomously at the enterprise level" — ⟨target⟩ by ⟨date⟩

Objective 3: Networks with executives, boards, regulators, and industry leaders, persuading and educating senior stakeholders on strategic data and AI priorities. [source: JFM responsibility (P7)]
KR1. From ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩ — tied to: "Networks with executives, boards, regulators, and industry leaders, persuading and educating senior stakeholders on strategic data and AI priorities."
KR2. Evidence at this level's complexity bar: "Industry-level, highly ambiguous problems" — ⟨target⟩ by ⟨date⟩

Objective 4: Provides high-level mentorship to senior and principal data scientists, shaping company-wide technical capability without direct reports. [source: JFM responsibility (P7)]
KR1. From ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩ — tied to: "Provides high-level mentorship to senior and principal data scientists, shaping company-wide technical capability without direct reports."
KR2. Evidence at this level's impact bar: "Enterprise-wide" — ⟨target⟩ by ⟨date⟩

Objective 5: Operates with complete independence, establishing the governance, ethics, and risk frameworks that define how AI systems are built and deployed. [source: JFM responsibility (P7)]
KR1. From ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩ — tied to: "Operates with complete independence, establishing the governance, ethics, and risk frameworks that define how AI systems are built and deployed."
KR2. Evidence at this level's decision rights bar: "Final technical authority across multiple domains" — ⟨target⟩ by ⟨date⟩

MBO areas

Key result areas from this level's responsibilities, each with a standard grounded in the canon leveling rubric where one exists.

Area	Standard	Target	Due
Sets direction for the data science function and anticipates emerging challenges, defining long-term AI/ML roadmaps that influence company-wide strategy and industry practice.	Consistent with this level's jfm knowledge-application rubric: "Develops new theories, models, and technologies that advance the field and define long-term company and industry data/AI roadmaps."	⟨target⟩	⟨date⟩
Solves precedent-free, ambiguous problems and develops new models, methods, or technologies with broad business and industry consequences.	Consistent with this level's jfm knowledge-application rubric: "Develops new theories, models, and technologies that advance the field and define long-term company and industry data/AI roadmaps."	⟨target⟩	⟨date⟩
Networks with executives, boards, regulators, and industry leaders, persuading and educating senior stakeholders on strategic data and AI priorities.	Consistent with this level's jfm knowledge-application rubric: "Develops new theories, models, and technologies that advance the field and define long-term company and industry data/AI roadmaps."	⟨target⟩	⟨date⟩
Provides high-level mentorship to senior and principal data scientists, shaping company-wide technical capability without direct reports.	Consistent with this level's jfm knowledge-application rubric: "Develops new theories, models, and technologies that advance the field and define long-term company and industry data/AI roadmaps."	⟨target⟩	⟨date⟩
Operates with complete independence, establishing the governance, ethics, and risk frameworks that define how AI systems are built and deployed.	Consistent with this level's jfm knowledge-application rubric: "Develops new theories, models, and technologies that advance the field and define long-term company and industry data/AI roadmaps."	⟨target⟩	⟨date⟩

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1. Area: Sets direction for the data science function and anticipates emerging challenges, defining long-term AI/ML roadmaps that influence company-wide strategy and industry practice.  [source: JFM responsibility (P7) — reused, no distinct responsibility content]
   Standard: Consistent with this level's jfm knowledge-application rubric: "Develops new theories, models, and technologies that advance the field and define long-term company and industry data/AI roadmaps."
   Target:   ⟨target⟩   Due: ⟨date⟩

2. Area: Solves precedent-free, ambiguous problems and develops new models, methods, or technologies with broad business and industry consequences.  [source: JFM responsibility (P7) — reused, no distinct responsibility content]
   Standard: Consistent with this level's jfm knowledge-application rubric: "Develops new theories, models, and technologies that advance the field and define long-term company and industry data/AI roadmaps."
   Target:   ⟨target⟩   Due: ⟨date⟩

3. Area: Networks with executives, boards, regulators, and industry leaders, persuading and educating senior stakeholders on strategic data and AI priorities.  [source: JFM responsibility (P7) — reused, no distinct responsibility content]
   Standard: Consistent with this level's jfm knowledge-application rubric: "Develops new theories, models, and technologies that advance the field and define long-term company and industry data/AI roadmaps."
   Target:   ⟨target⟩   Due: ⟨date⟩

4. Area: Provides high-level mentorship to senior and principal data scientists, shaping company-wide technical capability without direct reports.  [source: JFM responsibility (P7) — reused, no distinct responsibility content]
   Standard: Consistent with this level's jfm knowledge-application rubric: "Develops new theories, models, and technologies that advance the field and define long-term company and industry data/AI roadmaps."
   Target:   ⟨target⟩   Due: ⟨date⟩

5. Area: Operates with complete independence, establishing the governance, ethics, and risk frameworks that define how AI systems are built and deployed.  [source: JFM responsibility (P7) — reused, no distinct responsibility content]
   Standard: Consistent with this level's jfm knowledge-application rubric: "Develops new theories, models, and technologies that advance the field and define long-term company and industry data/AI roadmaps."
   Target:   ⟨target⟩   Due: ⟨date⟩

Scorecard

Only perspectives with real canon backing are shown — no Financial or Customer perspective, since nothing in the canon grounds business-financial or customer measures for a role alone.

Internal process

"Sets direction for the data science function and anticipates emerging challenges, defining long-term AI/ML roadmaps that influence company-wide strategy and industry practice."→ ⟨target⟩ by ⟨date⟩
"Solves precedent-free, ambiguous problems and develops new models, methods, or technologies with broad business and industry consequences."→ ⟨target⟩ by ⟨date⟩
"Networks with executives, boards, regulators, and industry leaders, persuading and educating senior stakeholders on strategic data and AI priorities."→ ⟨target⟩ by ⟨date⟩
"Provides high-level mentorship to senior and principal data scientists, shaping company-wide technical capability without direct reports."→ ⟨target⟩ by ⟨date⟩
"Operates with complete independence, establishing the governance, ethics, and risk frameworks that define how AI systems are built and deployed."→ ⟨target⟩ by ⟨date⟩

Role calibration

Meets the scope bar: "Cross-organization / enterprise technical strategy"→ ⟨target⟩ by ⟨date⟩
Meets the autonomy bar: "Operates autonomously at the enterprise level"→ ⟨target⟩ by ⟨date⟩
Meets the complexity bar: "Industry-level, highly ambiguous problems"→ ⟨target⟩ by ⟨date⟩
Meets the impact bar: "Enterprise-wide"→ ⟨target⟩ by ⟨date⟩
Meets the decision rights bar: "Final technical authority across multiple domains"→ ⟨target⟩ by ⟨date⟩
Meets the leadership bar: "Sets technical direction org-wide; develops principals"→ ⟨target⟩ by ⟨date⟩

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Internal process
  - "Sets direction for the data science function and anticipates emerging challenges, defining long-term AI/ML roadmaps that influence company-wide strategy and industry practice."  →  ⟨target⟩ by ⟨date⟩   [source: JFM responsibility (P7)]
  - "Solves precedent-free, ambiguous problems and develops new models, methods, or technologies with broad business and industry consequences."  →  ⟨target⟩ by ⟨date⟩   [source: JFM responsibility (P7)]
  - "Networks with executives, boards, regulators, and industry leaders, persuading and educating senior stakeholders on strategic data and AI priorities."  →  ⟨target⟩ by ⟨date⟩   [source: JFM responsibility (P7)]
  - "Provides high-level mentorship to senior and principal data scientists, shaping company-wide technical capability without direct reports."  →  ⟨target⟩ by ⟨date⟩   [source: JFM responsibility (P7)]
  - "Operates with complete independence, establishing the governance, ethics, and risk frameworks that define how AI systems are built and deployed."  →  ⟨target⟩ by ⟨date⟩   [source: JFM responsibility (P7)]

Role calibration
  - Meets the scope bar: "Cross-organization / enterprise technical strategy"  →  ⟨target⟩ by ⟨date⟩   [source: level dimension (Scope)]
  - Meets the autonomy bar: "Operates autonomously at the enterprise level"  →  ⟨target⟩ by ⟨date⟩   [source: level dimension (Autonomy)]
  - Meets the complexity bar: "Industry-level, highly ambiguous problems"  →  ⟨target⟩ by ⟨date⟩   [source: level dimension (Complexity)]
  - Meets the impact bar: "Enterprise-wide"  →  ⟨target⟩ by ⟨date⟩   [source: level dimension (Impact)]
  - Meets the decision rights bar: "Final technical authority across multiple domains"  →  ⟨target⟩ by ⟨date⟩   [source: level dimension (Decision rights)]
  - Meets the leadership bar: "Sets technical direction org-wide; develops principals"  →  ⟨target⟩ by ⟨date⟩   [source: level dimension (Leadership)]