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Data & AI practice lead --CHODC

Job in Princeton, Mercer County, New Jersey, 08543, USA
Listing for: Compunnel Inc.
Full Time position
Listed on 2026-03-01
Job specializations:
  • IT/Tech
    AI Engineer, Data Science Manager
Salary/Wage Range or Industry Benchmark: 60000 - 80000 USD Yearly USD 60000.00 80000.00 YEAR
Job Description & How to Apply Below
Position: Data & AI practice lead --CHODC5733559

Lead the end-to-end Data & AI practice engine, build market-ready offers, drive cross-sell into priority accounts, shape and win pursuits, and run a profitable delivery model. This is a builder/operator role with practice-level accountability across GTM, solutions, and execution quality.

Key Responsibilities
  • Create & Take Offers to Market: define signature offers, reference architectures, pricing guardrails, and playbooks.
  • Proactive GTM & Cross-sell: drive account insertion, industry narratives, workshops/POVs, and pursuit solutioning.
  • Delivery & Profitability: ensure GM protection, estimation discipline, utilization/pyramid health, and delivery governance.
  • IP & Accelerators: build reusable assets (accelerators, templates, demo kits) to improve win-rate and delivery efficiency.
  • Team & Partner Ecosystem: grow a strong team; drive partner co-sell motions and enablement.
Areas of Expertise / Exposure
  • Data platforms & engineering
  • Applied AI / GenAI solutions (RAG/copilots, evaluation, guardrails)
  • Data governance & trust (quality, lineage, privacy/security-by-design)
Success Metrics (summary KPIs)
  • Growth: bookings + qualified pipeline + win-rate; cross-sell penetration in priority accounts
  • Conversion engine: workshops/POVs and POV to program conversion; proposal turnaround and reuse
  • Profitability & delivery: GM at booking and realization; estimation variance/leakage control; delivery CSAT
  • Scalability: IP adoption; certifications/partner progress; leadership bench and retention
Experience
  • 12–18+ years in data/analytics/AI (services/product engineering), with 5+ years in practice/portfolio leadership.
  • Strong solutioning and estimation discipline; ability to run C-level discovery and shape deals.
  • Depth in at least 2–3 areas: data platforms, data engineering, analytics, AI/GenAI, MLOps/LLMOps, governance.
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