Note: The job is a remote job and is open to candidates in USA. Dice is seeking a Data Scientist to transform structured and unstructured data into actionable insights supporting product strategy, operational excellence, and customer outcomes. The role develops statistical, machine learning, and AI-enabled solutions, including Generative AI, LLM, and RAG capabilities, while partnering with cross-functional teams to improve decision-making, workflows, and customer experiences.
Responsibilities
- Contribute to AI-enabled products and operational initiatives across the VALUE portfolio
- Support experimentation and implementation of Generative AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG) capabilities
- Assist in the development and evaluation of prompts, knowledge retrieval strategies, model outputs, and AI-assisted workflows
- Build and monitor evaluation frameworks that measure AI accuracy, relevance, reliability, latency, and business impact
- Partner with engineering teams to integrate AI capabilities into production-ready services and platforms
- Help establish best practices for responsible AI, model monitoring, governance, transparency, and human oversight
- Develop, validate, and maintain statistical and machine learning models that support VALUE business objectives
- Apply predictive analytics, classification, forecasting, clustering, recommendation, and optimization techniques where appropriate
- Evaluate model performance and continuously refine solutions using measurable outcomes and stakeholder feedback
- Ensure model quality through testing, validation, documentation, and performance monitoring
- Partner with Product Managers and Business Analysts to translate business questions into analytical solutions
- Collaborate across Engineering, Product, Architecture, and Operations teams to maximize data-driven decision making
- Effectively communicate technical findings, assumptions, risks, and recommendations to diverse audiences
- Share knowledge and mentor peers through collaboration, documentation, and technical discussions
- Analyze large, complex datasets to identify trends, patterns, risks, and opportunities
- Transform raw data into actionable recommendations that support business and product decisions
- Develop dashboards, visualizations, reports, and analytical models that communicate effectively to technical and non-technical stakeholders
- Define metrics, KPIs, and measurement frameworks to evaluate product and business performance
- Perform exploratory analysis and hypothesis testing to validate assumptions and inform strategic decisions
Skills
- 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
- Data analysis, statistical modeling, and machine learning
- Python-based analytics and solution development
- Data visualization and insight communication
- KPI development, measurement frameworks, and business analysis
- Cross-functional collaboration with Product, Engineering, and stakeholders
- Strong problem-solving, critical thinking, and communication skills
- Data quality, governance, and responsible AI practices
- Experience with cloud-based analytics platforms (Azure preferred)
- Generative AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG)
- AI evaluation, experimentation, and continuous learning mindset
Benefits
- This position is eligible to participate in an annual incentive program.
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