Note: The job is a remote job and is open to candidates in USA. Dice is seeking Data Scientists who are passionate about solving complex data challenges using large-scale datasets and modern analytical tools. The role involves developing predictive models, leveraging AI, and collaborating with cross-functional teams to drive data-driven decision-making and deliver actionable insights.
Responsibilities
- Develop and enhance predictive models to improve customer experiences, revenue generation, business insights, advertising effectiveness, and other strategic outcomes
- Apply creative problem-solving and data science techniques to address complex business challenges and uncover actionable opportunities
- Leverage AI-assisted development tools (e.g., GitHub Copilot, Claude Code, Cline, OpenAI Codex) to accelerate analytics and software development workflows
- Apply data science and Generative AI techniques to analyze transaction and business data and deliver actionable insights
- Build agentic AI systems incorporating multi-step reasoning, tool usage, and memory capabilities for complex decision-making workflows
- Collaborate with cross-functional teams to guide data-driven decision-making and strategic recommendations
- Present analytical findings and recommendations to clients and stakeholders
- Create compelling visualizations and dashboards that communicate complex analyses effectively
- Identify opportunities to transform analytical solutions into scalable products that can benefit multiple clients
- Partner with business and technology teams to explore innovative uses of data to solve business problems
Skills
- 2 years of work experience with a Bachelor's degree, or
- An Advanced Degree (e.g., Master's, MBA, JD, MD, or PhD)
- 3+ years of work experience with a Bachelor's degree, or
- 2+ years of work experience with an Advanced Degree
- 2+ years of experience in data-driven decision-making, quantitative analysis, or related analytical functions, including exposure to LLMs and Generative AI applications
- Bachelor's degree in Statistics, Operations Research, Economics, Computer Science, Mathematics, Engineering, or a related analytical discipline. Advanced degrees are preferred
- Experience analyzing data using Python or other statistical programming languages
- Experience extracting, transforming, and analyzing large datasets using SQL, Hive, Spark, or similar technologies
- Strong understanding of machine learning techniques and associated libraries/frameworks
- Experience with LLM orchestration frameworks (e.g., LangChain or similar), vector databases, embedding models, and Generative AI solutions
- Proficiency in Excel, PowerPoint, Tableau, or equivalent data visualization tools
- Prior experience in financial services, payments, credit cards, banking, or merchant analytics is preferred but not required
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