We are seeking a highly analytical and business-focused Data Scientist for a high-visibility, internal AI initiative focused on building a real-time 'in-call' decision support engine. This role will improve pricing consistency, operational efficiency, and margin performance by transforming fragmented data into actionable pricing intelligence and automated content generation (e.g., automated job descriptions) that integrates with sales communications.

This is a high-impact opportunity for someone who enjoys building solutions from the ground up and working cross-functionally with sales, operations, and leadership teams to influence business decisions through data.

Key Responsibilities

• Design and implement real-time, LLM-driven engines that listen to client interactions to provide live pricing and resource recommendations
• Develop automated, context-aware content generation tools to create custom job descriptions on-the-fly during client calls
• Collaborate directly with the existing Data Science/App Dev team (currently deploying similar solutions for hardware resell) and the executive steering committee to drive this pilot to production
• Leverage internal, partner, and market data sources to train and refine AI models for live deployment
• Inventory, assess, and integrate multiple data sources including historical pricing, partner/vendor quotes, and market benchmarks
• Build and maintain centralized pricing and analytics data models
• Design and develop pricing models to support margin optimization and pricing consistency
• Create segmentation frameworks based on role, seniority, geography, and engagement type
• Support job description standardization and data quality initiatives
• Develop pricing insights, tools, and reporting to support business stakeholders
• Assist in establishing pricing governance frameworks including pricing thresholds and approval workflows
• Collaborate closely with sales, operations, and resource management teams to drive data-driven decision making

Required Qualifications

• Bachelor’s or Master’s degree in Data Science, Statistics, Mathematics, Computer Science, or related field
• Experience in data modeling, analytics, and machine learning
• Strong programming skills in Python, SQL, and/or R
• Experience working with large and complex datasets
• Strong analytical and problem-solving skills
• Ability to communicate technical insights effectively to non-technical stakeholders

Preferred Qualifications

• Experience in pricing analytics, consulting, staffing, or services-based organizations
• Familiarity with market pricing benchmarks and rate analysis
• Experience with machine learning deployment and data pipelines
• Experience building reporting dashboards or decision-support tools

Success Metrics

• Delivery of a unified pricing and analytics dataset
• Development of pricing frameworks and rate guidance models
• Improved pricing consistency and business adoption
• Deployment of initial predictive or analytical pricing models