← Data Science — P6

Goal templates — Data Science — P6

Data Science & Analytics · Data Science · P6 — Principal 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 (P6)

Defines which projects should exist and figures out which questions the business should be asking; serves as strategic mind and high-level technical architect.

Specific
Deliver: "Defines which projects should exist and figures out which questions the business should be asking; serves as strategic mind and high-level technical architect."
Measurable
Move the metric this drives from ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩.
Achievable
Scoped to this level's jfm complexity/problem-solving rubric: "Solves field-shaping problems — defining which questions matter, weighing platform and deployment trade-offs, and assessing AI risk."
Relevant
Advances the Data Science & Analytics · Data Science mandate for a P6 — Principal Professional.
Time-bound
⟨date⟩

JFM responsibility (P6)

Provides technical leadership through influence and mentorship rather than people management, shaping the organization's data science capability.

Specific
Deliver: "Provides technical leadership through influence and mentorship rather than people management, shaping the organization's data science capability."
Measurable
Move the metric this drives from ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩.
Achievable
Scoped to this level's jfm complexity/problem-solving rubric: "Solves field-shaping problems — defining which questions matter, weighing platform and deployment trade-offs, and assessing AI risk."
Relevant
Advances the Data Science & Analytics · Data Science mandate for a P6 — Principal Professional.
Time-bound
⟨date⟩

JFM responsibility (P6)

Influences architectural direction and weighs trade-offs in platform design and ML deployment across the organization.

Specific
Deliver: "Influences architectural direction and weighs trade-offs in platform design and ML deployment across the organization."
Measurable
Move the metric this drives from ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩.
Achievable
Scoped to this level's jfm complexity/problem-solving rubric: "Solves field-shaping problems — defining which questions matter, weighing platform and deployment trade-offs, and assessing AI risk."
Relevant
Advances the Data Science & Analytics · Data Science mandate for a P6 — Principal Professional.
Time-bound
⟨date⟩

JFM responsibility (P6)

Guides senior leadership on the long-term direction of AI/ML capabilities, aligning technical decisions with product vision, company goals, and regulatory constraints.

Specific
Deliver: "Guides senior leadership on the long-term direction of AI/ML capabilities, aligning technical decisions with product vision, company goals, and regulatory constraints."
Measurable
Move the metric this drives from ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩.
Achievable
Scoped to this level's jfm complexity/problem-solving rubric: "Solves field-shaping problems — defining which questions matter, weighing platform and deployment trade-offs, and assessing AI risk."
Relevant
Advances the Data Science & Analytics · Data Science mandate for a P6 — Principal Professional.
Time-bound
⟨date⟩

JFM responsibility (P6)

Assesses the risk of AI systems and research investments, operating at the intersection of deep technical depth and business strategy.

Specific
Deliver: "Assesses the risk of AI systems and research investments, operating at the intersection of deep technical depth and business strategy."
Measurable
Move the metric this drives from ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩.
Achievable
Scoped to this level's jfm complexity/problem-solving rubric: "Solves field-shaping problems — defining which questions matter, weighing platform and deployment trade-offs, and assessing AI risk."
Relevant
Advances the Data Science & Analytics · Data Science mandate for a P6 — Principal Professional.
Time-bound
⟨date⟩
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1. Defines which projects should exist and figures out which questions the business should be asking; serves as strategic mind and high-level technical architect.  [source: JFM responsibility (P6)]
   Specific:    Deliver: "Defines which projects should exist and figures out which questions the business should be asking; serves as strategic mind and high-level technical architect."
   Measurable:  Move the metric this drives from ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩.
   Achievable:  Scoped to this level's jfm complexity/problem-solving rubric: "Solves field-shaping problems — defining which questions matter, weighing platform and deployment trade-offs, and assessing AI risk."
   Relevant:    Advances the Data Science & Analytics · Data Science mandate for a P6 — Principal Professional.
   Time-bound:  ⟨date⟩

2. Provides technical leadership through influence and mentorship rather than people management, shaping the organization's data science capability.  [source: JFM responsibility (P6)]
   Specific:    Deliver: "Provides technical leadership through influence and mentorship rather than people management, shaping the organization's data science capability."
   Measurable:  Move the metric this drives from ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩.
   Achievable:  Scoped to this level's jfm complexity/problem-solving rubric: "Solves field-shaping problems — defining which questions matter, weighing platform and deployment trade-offs, and assessing AI risk."
   Relevant:    Advances the Data Science & Analytics · Data Science mandate for a P6 — Principal Professional.
   Time-bound:  ⟨date⟩

3. Influences architectural direction and weighs trade-offs in platform design and ML deployment across the organization.  [source: JFM responsibility (P6)]
   Specific:    Deliver: "Influences architectural direction and weighs trade-offs in platform design and ML deployment across the organization."
   Measurable:  Move the metric this drives from ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩.
   Achievable:  Scoped to this level's jfm complexity/problem-solving rubric: "Solves field-shaping problems — defining which questions matter, weighing platform and deployment trade-offs, and assessing AI risk."
   Relevant:    Advances the Data Science & Analytics · Data Science mandate for a P6 — Principal Professional.
   Time-bound:  ⟨date⟩

4. Guides senior leadership on the long-term direction of AI/ML capabilities, aligning technical decisions with product vision, company goals, and regulatory constraints.  [source: JFM responsibility (P6)]
   Specific:    Deliver: "Guides senior leadership on the long-term direction of AI/ML capabilities, aligning technical decisions with product vision, company goals, and regulatory constraints."
   Measurable:  Move the metric this drives from ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩.
   Achievable:  Scoped to this level's jfm complexity/problem-solving rubric: "Solves field-shaping problems — defining which questions matter, weighing platform and deployment trade-offs, and assessing AI risk."
   Relevant:    Advances the Data Science & Analytics · Data Science mandate for a P6 — Principal Professional.
   Time-bound:  ⟨date⟩

5. Assesses the risk of AI systems and research investments, operating at the intersection of deep technical depth and business strategy.  [source: JFM responsibility (P6)]
   Specific:    Deliver: "Assesses the risk of AI systems and research investments, operating at the intersection of deep technical depth and business strategy."
   Measurable:  Move the metric this drives from ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩.
   Achievable:  Scoped to this level's jfm complexity/problem-solving rubric: "Solves field-shaping problems — defining which questions matter, weighing platform and deployment trade-offs, and assessing AI risk."
   Relevant:    Advances the Data Science & Analytics · Data Science mandate for a P6 — Principal 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 (P6)

Defines which projects should exist and figures out which questions the business should be asking; serves as strategic mind and high-level technical architect.

  • From ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩ — tied to: "Defines which projects should exist and figures out which questions the business should be asking; serves as strategic mind and high-level technical architect."
  • Evidence at this level's scope bar: "Organization-wide architecture and the hardest problems" — ⟨target⟩ by ⟨date⟩

JFM responsibility (P6)

Provides technical leadership through influence and mentorship rather than people management, shaping the organization's data science capability.

  • From ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩ — tied to: "Provides technical leadership through influence and mentorship rather than people management, shaping the organization's data science capability."
  • Evidence at this level's autonomy bar: "Defines direction; minimal oversight" — ⟨target⟩ by ⟨date⟩

JFM responsibility (P6)

Influences architectural direction and weighs trade-offs in platform design and ML deployment across the organization.

  • From ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩ — tied to: "Influences architectural direction and weighs trade-offs in platform design and ML deployment across the organization."
  • Evidence at this level's complexity bar: "Strategic, open-ended problems shaping the technical future" — ⟨target⟩ by ⟨date⟩

JFM responsibility (P6)

Guides senior leadership on the long-term direction of AI/ML capabilities, aligning technical decisions with product vision, company goals, and regulatory constraints.

  • From ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩ — tied to: "Guides senior leadership on the long-term direction of AI/ML capabilities, aligning technical decisions with product vision, company goals, and regulatory constraints."
  • Evidence at this level's impact bar: "Organization-wide" — ⟨target⟩ by ⟨date⟩

JFM responsibility (P6)

Assesses the risk of AI systems and research investments, operating at the intersection of deep technical depth and business strategy.

  • From ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩ — tied to: "Assesses the risk of AI systems and research investments, operating at the intersection of deep technical depth and business strategy."
  • Evidence at this level's decision rights bar: "Sets technical strategy for a major area" — ⟨target⟩ by ⟨date⟩
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Objective 1: Defines which projects should exist and figures out which questions the business should be asking; serves as strategic mind and high-level technical architect.  [source: JFM responsibility (P6)]
  KR1. From ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩ — tied to: "Defines which projects should exist and figures out which questions the business should be asking; serves as strategic mind and high-level technical architect."
  KR2. Evidence at this level's scope bar: "Organization-wide architecture and the hardest problems" — ⟨target⟩ by ⟨date⟩

Objective 2: Provides technical leadership through influence and mentorship rather than people management, shaping the organization's data science capability.  [source: JFM responsibility (P6)]
  KR1. From ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩ — tied to: "Provides technical leadership through influence and mentorship rather than people management, shaping the organization's data science capability."
  KR2. Evidence at this level's autonomy bar: "Defines direction; minimal oversight" — ⟨target⟩ by ⟨date⟩

Objective 3: Influences architectural direction and weighs trade-offs in platform design and ML deployment across the organization.  [source: JFM responsibility (P6)]
  KR1. From ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩ — tied to: "Influences architectural direction and weighs trade-offs in platform design and ML deployment across the organization."
  KR2. Evidence at this level's complexity bar: "Strategic, open-ended problems shaping the technical future" — ⟨target⟩ by ⟨date⟩

Objective 4: Guides senior leadership on the long-term direction of AI/ML capabilities, aligning technical decisions with product vision, company goals, and regulatory constraints.  [source: JFM responsibility (P6)]
  KR1. From ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩ — tied to: "Guides senior leadership on the long-term direction of AI/ML capabilities, aligning technical decisions with product vision, company goals, and regulatory constraints."
  KR2. Evidence at this level's impact bar: "Organization-wide" — ⟨target⟩ by ⟨date⟩

Objective 5: Assesses the risk of AI systems and research investments, operating at the intersection of deep technical depth and business strategy.  [source: JFM responsibility (P6)]
  KR1. From ⟨baseline⟩ to ⟨target⟩ by ⟨date⟩ — tied to: "Assesses the risk of AI systems and research investments, operating at the intersection of deep technical depth and business strategy."
  KR2. Evidence at this level's decision rights bar: "Sets technical strategy for a major area" — ⟨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.

AreaStandardTargetDue
Defines which projects should exist and figures out which questions the business should be asking; serves as strategic mind and high-level technical architect.Consistent with this level's jfm knowledge-application rubric: "Shapes the organization's data science and AI/ML direction with visionary, field-influencing technical judgment and architectural authority."⟨target⟩⟨date⟩
Provides technical leadership through influence and mentorship rather than people management, shaping the organization's data science capability.Consistent with this level's jfm knowledge-application rubric: "Shapes the organization's data science and AI/ML direction with visionary, field-influencing technical judgment and architectural authority."⟨target⟩⟨date⟩
Influences architectural direction and weighs trade-offs in platform design and ML deployment across the organization.Consistent with this level's jfm knowledge-application rubric: "Shapes the organization's data science and AI/ML direction with visionary, field-influencing technical judgment and architectural authority."⟨target⟩⟨date⟩
Guides senior leadership on the long-term direction of AI/ML capabilities, aligning technical decisions with product vision, company goals, and regulatory constraints.Consistent with this level's jfm knowledge-application rubric: "Shapes the organization's data science and AI/ML direction with visionary, field-influencing technical judgment and architectural authority."⟨target⟩⟨date⟩
Assesses the risk of AI systems and research investments, operating at the intersection of deep technical depth and business strategy.Consistent with this level's jfm knowledge-application rubric: "Shapes the organization's data science and AI/ML direction with visionary, field-influencing technical judgment and architectural authority."⟨target⟩⟨date⟩
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1. Area: Defines which projects should exist and figures out which questions the business should be asking; serves as strategic mind and high-level technical architect.  [source: JFM responsibility (P6) — reused, no distinct responsibility content]
   Standard: Consistent with this level's jfm knowledge-application rubric: "Shapes the organization's data science and AI/ML direction with visionary, field-influencing technical judgment and architectural authority."
   Target:   ⟨target⟩   Due: ⟨date⟩

2. Area: Provides technical leadership through influence and mentorship rather than people management, shaping the organization's data science capability.  [source: JFM responsibility (P6) — reused, no distinct responsibility content]
   Standard: Consistent with this level's jfm knowledge-application rubric: "Shapes the organization's data science and AI/ML direction with visionary, field-influencing technical judgment and architectural authority."
   Target:   ⟨target⟩   Due: ⟨date⟩

3. Area: Influences architectural direction and weighs trade-offs in platform design and ML deployment across the organization.  [source: JFM responsibility (P6) — reused, no distinct responsibility content]
   Standard: Consistent with this level's jfm knowledge-application rubric: "Shapes the organization's data science and AI/ML direction with visionary, field-influencing technical judgment and architectural authority."
   Target:   ⟨target⟩   Due: ⟨date⟩

4. Area: Guides senior leadership on the long-term direction of AI/ML capabilities, aligning technical decisions with product vision, company goals, and regulatory constraints.  [source: JFM responsibility (P6) — reused, no distinct responsibility content]
   Standard: Consistent with this level's jfm knowledge-application rubric: "Shapes the organization's data science and AI/ML direction with visionary, field-influencing technical judgment and architectural authority."
   Target:   ⟨target⟩   Due: ⟨date⟩

5. Area: Assesses the risk of AI systems and research investments, operating at the intersection of deep technical depth and business strategy.  [source: JFM responsibility (P6) — reused, no distinct responsibility content]
   Standard: Consistent with this level's jfm knowledge-application rubric: "Shapes the organization's data science and AI/ML direction with visionary, field-influencing technical judgment and architectural authority."
   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

  • "Defines which projects should exist and figures out which questions the business should be asking; serves as strategic mind and high-level technical architect."→ ⟨target⟩ by ⟨date⟩
  • "Provides technical leadership through influence and mentorship rather than people management, shaping the organization's data science capability."→ ⟨target⟩ by ⟨date⟩
  • "Influences architectural direction and weighs trade-offs in platform design and ML deployment across the organization."→ ⟨target⟩ by ⟨date⟩
  • "Guides senior leadership on the long-term direction of AI/ML capabilities, aligning technical decisions with product vision, company goals, and regulatory constraints."→ ⟨target⟩ by ⟨date⟩
  • "Assesses the risk of AI systems and research investments, operating at the intersection of deep technical depth and business strategy."→ ⟨target⟩ by ⟨date⟩

Role calibration

  • Meets the scope bar: "Organization-wide architecture and the hardest problems"→ ⟨target⟩ by ⟨date⟩
  • Meets the autonomy bar: "Defines direction; minimal oversight"→ ⟨target⟩ by ⟨date⟩
  • Meets the complexity bar: "Strategic, open-ended problems shaping the technical future"→ ⟨target⟩ by ⟨date⟩
  • Meets the impact bar: "Organization-wide"→ ⟨target⟩ by ⟨date⟩
  • Meets the decision rights bar: "Sets technical strategy for a major area"→ ⟨target⟩ by ⟨date⟩
  • Meets the leadership bar: "Recognized authority; multiplies many teams"→ ⟨target⟩ by ⟨date⟩
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Internal process
  - "Defines which projects should exist and figures out which questions the business should be asking; serves as strategic mind and high-level technical architect."  →  ⟨target⟩ by ⟨date⟩   [source: JFM responsibility (P6)]
  - "Provides technical leadership through influence and mentorship rather than people management, shaping the organization's data science capability."  →  ⟨target⟩ by ⟨date⟩   [source: JFM responsibility (P6)]
  - "Influences architectural direction and weighs trade-offs in platform design and ML deployment across the organization."  →  ⟨target⟩ by ⟨date⟩   [source: JFM responsibility (P6)]
  - "Guides senior leadership on the long-term direction of AI/ML capabilities, aligning technical decisions with product vision, company goals, and regulatory constraints."  →  ⟨target⟩ by ⟨date⟩   [source: JFM responsibility (P6)]
  - "Assesses the risk of AI systems and research investments, operating at the intersection of deep technical depth and business strategy."  →  ⟨target⟩ by ⟨date⟩   [source: JFM responsibility (P6)]

Role calibration
  - Meets the scope bar: "Organization-wide architecture and the hardest problems"  →  ⟨target⟩ by ⟨date⟩   [source: level dimension (Scope)]
  - Meets the autonomy bar: "Defines direction; minimal oversight"  →  ⟨target⟩ by ⟨date⟩   [source: level dimension (Autonomy)]
  - Meets the complexity bar: "Strategic, open-ended problems shaping the technical future"  →  ⟨target⟩ by ⟨date⟩   [source: level dimension (Complexity)]
  - Meets the impact bar: "Organization-wide"  →  ⟨target⟩ by ⟨date⟩   [source: level dimension (Impact)]
  - Meets the decision rights bar: "Sets technical strategy for a major area"  →  ⟨target⟩ by ⟨date⟩   [source: level dimension (Decision rights)]
  - Meets the leadership bar: "Recognized authority; multiplies many teams"  →  ⟨target⟩ by ⟨date⟩   [source: level dimension (Leadership)]