Data Scientist or Senior Data Scientist

Position Overview

NRG is a leading global insights and strategy firm at the confluence of content, culture, and technology. In this role as a Data Scientist or Senior Data Scientist within the Marketing/Data Science team, you will design, build and scale AI/ML solutions that integrate cutting-edge GenAI innovations – such as fine-tuned LLMs, RAG pipelines, and agentic workflows – into our core research products. Collaborating with cross-functional teams, you will drive experimentation, productionize reliable ML solutions, and serve as a technical subject matter expert to empower innovative insights across entertainment, technology, and culture.

Key Responsibilities

• Design and execute advanced AI/ML models – including fine-tuned LLMs and RAG architectures – for integration into both internal tooling and client-facing products.
• Lead experimentation efforts: define hypotheses, design interpretable tests, analyze results rigorously, and communicate findings effectively.
• Serve as the technical SME for GenAI/LLM-powered tools, guiding architecture, model optimization, and deployment strategies.
• Collaborate with software and data engineering teams to productionize models and contribute to robust CI/CD pipelines with MLOps/LLMOps best practices.
• Stay current on emerging AI methods and apply innovations such as agentic workflows, memory-augmented systems, and multimodal embeddings in real-world applications.
• Promote AI adoption internally by educating cross-functional partners and continuously improving processes.
• Manage projects effectively, ensuring clear progress updates and proactive communication with collaborators.
• Write production-grade Python code to support models, pipelines, and experimental frameworks.
• Uphold a high degree of ethics and empathy in recognizing the potential disruptive nature of AI for organizations and individuals.

Required Qualifications

• 5+ years in data science, ML engineering, or related analytics roles.
• Proven experience deploying machine learning models into production environments, ideally with LLMs or GenAI systems.
• Bachelor’s or higher degree in a quantitative field (e.g., Computer Science, Engineering, Statistics, Mathematics).
• Experience working with consumer data, particularly within media, entertainment, or marketing research contexts.
• Proficiency with modern ML frameworks and GenAI stacks (e.g., LangChain/LlamaIndex, HuggingFace Transformers, OpenAI APIs).
• Experience building and fine-tuning models using domain-specific datasets, including survey or behavioral data.
• Familiarity with retrieval-augmented generation (RAG), vector databases, and multi-step reasoning workflows.
• Strong implementation of MLOps/LLMOps practices including version control, experiment tracking, and model monitoring.
• Excellent communication skills to distill technical complexity for non-technical stakeholders.
• Highly organized and dependable with a proven track record of managing multiple high-stakes priorities.

Benefits & Perks

• Flexible/Remote work with optional usage of our offices in Playa Vista or New York.
• Unlimited PTO, volunteer days, and generous recharge days (including a full office closure during the week of Christmas and New Year’s).
• Medical, Dental, and Vision Insurance Plans.
• 401K with company match.
• Generous paid Parental Leave.
• Regular performance evaluations with opportunities for promotions and merit increases.
• Educational and training reimbursement plan along with professional development opportunities.
• Employee perks program, including discounts on travel, hotels, cars, fitness, movie tickets, and more.
• Resources for mental health, inclusive care, and family building.
• NRGratitude – our company-wide employee recognition program.
• Regular team and company events, including annual summer and holiday parties.
• Pet-friendly headquarters and pet insurance options.

Compensation

In order to comply with equal pay and salary transparency laws, the target range of base compensation for this role in the United States is $110,000 - $170,000. Actual compensation will depend on factors such as skill set, experience level, and geographical location.