Specialist, Data Scientist

Quick Facts

IC20 Emerging Specialist data science role delivering analytics, machine learning, and AI-enabled capabilities for VALUE products, customers, and business outcomes. Owns moderately complex data science initiatives end-to-end—from problem definition through implementation and continuous improvement.

Description

As a Data Scientist on the VALUE team, you will transform data into actionable insights that drive product strategy, operational excellence, and customer outcomes. Analyze structured and unstructured data, develop statistical and machine learning solutions, and communicate findings through clear visualizations, reporting, and recommendations. Partner closely with Product Managers, Software Engineers, Business Analysts, Data Engineers, and Quality Engineers to improve decision-making, automate workflows, enhance customer experiences, and create measurable business value—also contributing to Generative AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG).

Responsibilities

AI & Emerging Technology Contributions (40%)

• Contribute to AI-enabled products and operational initiatives across the VALUE portfolio
• Support experimentation and implementation of Generative AI, LLMs, and RAG capabilities
• Develop and evaluate prompts, knowledge retrieval strategies, model outputs, and AI-assisted workflows
• Build and monitor evaluation frameworks measuring AI accuracy, relevance, reliability, latency, and business impact
• Partner with engineering teams to integrate AI capabilities into production-ready services and platforms
• Establish best practices for responsible AI, model monitoring, governance, transparency, and human oversight

Statistical Modeling & Machine Learning (30%)

• Develop, validate, and maintain statistical and machine learning models for VALUE business objectives
• Use predictive analytics, classification, forecasting, clustering, recommendation, and optimization techniques as appropriate
• Evaluate model performance and refine solutions using measurable outcomes and stakeholder feedback
• Ensure model quality through testing, validation, documentation, and performance monitoring

Collaboration (20%)

• Translate business questions into analytical solutions with Product Managers and Business Analysts
• Collaborate across Engineering, Product, Architecture, and Operations to maximize data-driven decisions
• Communicate technical findings, assumptions, risks, and recommendations to diverse audiences
• Share knowledge and mentor peers via documentation and technical discussions

Data Analysis & Insights (10%)

• Analyze large, complex datasets to identify trends, patterns, risks, and opportunities
• Transform raw data into actionable recommendations for business and product decisions
• Develop dashboards, visualizations, reports, and analytical models for technical and non-technical stakeholders
• Define metrics, KPIs, and measurement frameworks to evaluate product and business performance
• Perform exploratory analysis and hypothesis testing

Benefits

Compensation is influenced by skill set, experience, and location. The full-time salary range is $125,000 – $140,000, and the position is eligible for an annual incentive program. Information on benefits can be found here.

Requirements

• Bachelor’s degree in data science, Statistics, Mathematics, Computer Science, Engineering, Analytics, or related field OR equivalent practical experience
• 3+ years of experience in data science, advanced analytics, machine learning, or related analytical roles
• Demonstrated experience using Python for data analysis, modeling, and automation
• Experience with statistical analysis, exploratory data analysis, and predictive modeling
• Experience working within Agile product or engineering teams
• Knowledge of data quality, governance, and responsible AI practices
• Experience with cloud-based analytics platforms (Azure preferred)
• Experience with Generative AI, LLMs, and Retrieval-Augmented Generation (RAG); AI evaluation and experimentation