Data Scientist, NLP & GenAI – Model Development

Our client is hiring Data Scientists, NLP & GenAI – Model Development

Join an AI-Powered Consumer Intelligence Platform Delivering Insights for the World’s Biggest Brands

Company Background

We're an AI-powered consumer intelligence platform that transforms billions of data points -- Google searches, social conversations, product reviews, and videos -- into strategic insights for Fortune 500 clients in CPG, beverages, and personal care. We deliver in days what traditional research takes months to produce.

The Role

As a Data Scientist, you'll build NLP models and GenAI solutions that extract meaning from massive consumer datasets.Your work will power two core products in brand measurement and product innovation insights. You'll develop sentiment analysis, emotion detection, and LLM-based applications that directly inform multi-million dollar marketing and product decisions for global brands. This is a remote position reporting to our CTO.

What You'll Do

• Develop and deploy NLP models for sentiment analysis, emotion detection, and text classification processing 1M+ documents daily

• Design and implement LLM-based solutions using prompt engineering, RAG architectures, and fine-tuning approaches

• Build evaluation frameworks to measure model accuracy, establishing baselines and tracking improvements

• Collaborate with data engineers and AI engineers to productionize models via API endpoints and batch pipelines

• Work with multi-language text data (English primary, with global market expansion)

• Translate business requirements into technical model specifications

• Document model architectures, performance metrics, and usage guidelines for cross-functional teams

• Iterate on models based on client feedback and production performance data

• Core Stack: Python, SQL

• AI/ML: Sentiment analysis, emotion detection, LLMs, GenAI, prompt engineering

• NLP Libraries: Modern frameworks (Hugging Face, transformers, Spacy, NLTK, LangChain, LLM APIs)

• Cloud & Data: Azure ecosystem, Databricks, large-scale datasets

• Products: brand measurement and product development innovation products

What We're Looking For

Education

• Bachelor's degree in Computer Science, Statistics, Mathematics, or related quantitative field

Experience

• 4+ years in data science/machine learning roles with production model development

• 2+ years focused primarily on NLP tasks (sentiment analysis, classification, topic modeling, or similar)

• 1+ years working with LLMs (prompt engineering, fine-tuning, or RAG implementations)

• Minimum 1 model deployed to production or demonstrably used to inform business decisions

Technical Skills

• Python: 3+ years in production ML environments

• ML/NLP libraries: Proficiency with at least 2 of (scikit-learn, Hugging Face Transformers, SpaCy, NLTK)

• SQL: Intermediate level (JOINs, aggregations, window functions for datasets >1M rows)

• Version control: Git-based workflows including code reviews and collaborative development

Working Style

• Experience handing off models to engineering teams for deployment

• Track record of self-directed work with minimal daily supervision

• Clear written communication for technical documentation

Preferred (Nice to Have)

• Master's or PhD in relevant quantitative field

• Experience with Azure cloud platform and/or Databricks

• LangChain or similar LLM orchestration framework experience

• PySpark or distributed computing experience

• Multi-language NLP experience (processing text beyond English)

• Consumer insights, CPG, or marketing analytics industry background

• Emotion detection model development specifically

• MLOps experience (model monitoring, A/B testing, automated retraining)

What We Offer

• Competitive base salary (with performance bonus + equity participation opportunities)

• Fully remote (4 hours overlap with US Eastern time zone desired)

• Environment: Greenfield development—modern tech stack, no legacy code constraints

• Impact: Your models directly power products used by Fortune 500 clients

• Growth: Work with cutting-edge GenAI and LLM technologies

• Team: Collaborate with senior data scientists, data engineers, and AI engineers in a flat structure