Remote NLP Data Scientist (New York City-Based)

Annual Salary: $119,596

Join a Mission-Driven, Data-Centric Team Empowering AI Innovation

Are you passionate about natural language processing and how it reshapes how organizations interpret and act on human language? Do you want to work remotely but still be part of a vibrant, tech-savvy New York City data science team? This opportunity is for skilled NLP professionals eager to build models that drive intelligent automation, real-time sentiment analysis, and language-driven insights across enterprise systems.

We seek an NLP Data Scientist with experience in deep learning, machine learning algorithms, and linguistic data analysis. You'll join a forward-thinking organization using cutting-edge tools to develop and deploy large-scale language models, making tangible impacts in customer experience, fraud detection, and predictive analytics. This role also offers a rare chance to contribute to transformative solutions across healthcare, finance, and e-commerce sectors—all from the comfort of your remote workspace. Your efforts will influence decisions at scale, driving smarter, more intuitive interactions between humans and machines.

Key Responsibilities for the Remote NLP Data Scientist Role

Develop and Optimize Language Models

• Design, train, and evaluate natural language understanding (NLU) and natural language generation (NLG) models
• Optimize transformer-based architectures (e.g., BERT, RoBERTa, GPT variants) for real-world applications.

Extract and Interpret Text Data Insights

• Analyze unstructured text data to extract business insights and inform strategy.
• Utilize advanced NLP methods including entity extraction, thematic analysis, text segmentation, and emotion recognition.

Collaborate with Cross-Functional Teams

• Collaborate regularly with specialists in data infrastructure, product development, and artificial intelligence.
• Integrate NLP solutions into scalable machine learning pipelines

Ensure Performance and Reliability

• Conduct A/B testing and performance validation using model interpretability tools.
• Translate complex research into actionable, production-ready solutions

Tools, Technologies, and Frameworks Used

Programming Languages and Libraries

• Python with spaCy, Hugging Face Transformers, NLTK, PyTorch, TensorFlow, Scikit-learn

Cloud Infrastructure and DevOps Tools

• AWS S3, Lambda, SageMaker
• Docker, Kubernetes, GitHub Actions

Data Engineering Platforms

• Apache Spark, Snowflake, Pandas, SQL (PostgreSQL preferred)

Machine Learning Lifecycle Management

• MLflow, Weights & Biases, Airflow, DVC

Monitoring and Testing

• Prometheus, Grafana, pytest, Great Expectations

Remote Work Culture and Environment

Remote-First Collaboration

• Structured agile rituals, virtual whiteboard sessions, and peer code reviews
• Async-friendly, documentation-first, and impact-driven work culture

Geographic and Time Zone Considerations

• Candidates must reside in the U.S.
• Preference for those available during Eastern Time working hours

Team Dynamics and Diversity

• Agile squads of 5–7 members
• Commitment to inclusive hiring practices and diverse teams

Measurable Impact and Innovation at Scale

Quantifiable Achievements

• +42% increase in sentiment analysis accuracy from BERT optimization
• 4x faster NLP model deployment via modular MLOps

• 97% precision across multilingual production datasets

Real-World Applications

• Human-like chatbot fluency
• Enhanced call center routing using semantic understanding
• Improved product search relevance through contextual query embeddings

Qualifications and Candidate Profile

Educational and Professional Background

• Bachelor’s degree in Computer Science, Computational Linguistics, or related field (Master’s or Ph.D. preferred)
• 3+ years in data science or machine learning with NLP specialization

Technical Expertise

• Proficiency in Python and associated data science libraries
• Knowledge of dependency parsing, POS tagging, embeddings, and transfer learning

Deployment and Communication Skills

• Familiarity with REST APIs, containerized environments
• Practical interpersonal abilities to translate complex technical details into clear, actionable business insights

Career Growth and Development Opportunities

Professional Development Resources

• Conference budgets for ACL, NeurIPS, and EMNLP
• Monthly innovation days for tool experimentation

Career Path Flexibility

• Opportunities to explore research, product, or engineering tracks
• Roles in model governance, explainability, and multilingual NLP optimization

Call to Action: Transform the Future of Language AI

Step into a role where your work directly advances the boundaries of machine learning and linguistic intelligence. Here, you won't just build models—you'll shape real-world systems that understand people, scale to billions of words, and create intuitive user experiences.

Become the architect of the next generation of language AI.

📩 Apply today and turn complex language into clear impact.