Sales Strategy & Data Analytics: GTM Decision Intelligence Quantitative Analyst

Sales Strategy & Data Analytics: GTM Decision Intelligence Quantitative Analyst - US Remote

NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization,

NTT DATA North America is seeking a GTM Decision Intelligence Quantitative Analyst to develop, test, explain, operationalize, and improve evidence-based go-to-market recommendations for sales leaders and sellers. The Analyst combines bookings, market data, account plans, partner targets and offerings, internal solutions, sales plays, industry points of view, and historical outcomes using quantitative methods and approved AI capabilities. The role converts fragmented information into prioritized account-partner-solution opportunities and next-best-motion recommendations without replacing seller judgment or Solution & Strategy content ownership.

Responsibilities Include :

Analytical Design and Data Fusion

Frame ambiguous commercial questions as testable analytical problems, data requirements, features, hypotheses, acceptance criteria, and experiments.
Combine structured and unstructured internal and external data into governed, analysis-ready features with documented lineage and limitations.
Design account-solution-partner-fit, whitespace, propensity, relevance, timing, and next-best-motion methods.
Use approved AI capabilities for synthesis, classification, comparison, research acceleration, and analytical workflow orchestration while preserving human review and source traceability.

Recommendation Engine and Validation

Develop and maintain recommendation scoring logic, confidence thresholds, prompts, transformations, business rules, versions, and controlled release criteria.
Test recommendations against known outcomes, holdout samples, business rules, edge cases, stakeholder challenge, and observed field outcomes.
Assess coverage, missing data, skew, instability, drift, unintended bias, false precision, and model risk; elevate material concerns before use.
Create explainable recommendation outputs that communicate supporting evidence, confidence, assumptions, limitations, and suggested seller action.

Cross-Tower Collaboration and Learning

Partner with Solution & Strategy for governed solution, sales-play, offering, and industry-content inputs.
Partner with the Sales Tower for seller context, business validation, recommendation release, field activation, and feedback.
Capture recommendation disposition, seller feedback, opportunity progression, and observed outcomes to improve methods without overstating causality.
Operationalize repeatable analytical workflows with KPI Reporting, Analytics Shared Services, Data and AI teams, and responsible-AI stakeholders.

Qualifications:

Bachelor's or advanced degree in statistics, economics, operations research, data science, computer science, engineering, applied mathematics, business analytics, or a related field, or equivalent practical experience.
Experience translating business questions into quantitative analysis, scoring methods, experiments, or recommendation systems.
Proficiency with SQL, Python or comparable analytical tools, plus strong Excel and business-intelligence skills.
Experience using AI-assisted analytical workflows with source traceability, validation, human review, and responsible-AI controls.
Strong knowledge of feature design, validation, explainability, data quality, bias and drift considerations, and analytical documentation.
Ability to build broad knowledge across partner ecosystems, industries, solutions, sales motions, market signals, account planning, and commercial performance.
Strong communication skills and ability to influence senior sales, strategy, data, and…