Natural Language Processing (NLP) Data Scientist

Remote Full-time
We are looking for a motivated and detail-oriented NLP Data Scientist with a passion for text mining, machine learning, and natural language processing. This role offers the opportunity to apply advanced NLP techniques to drive innovation and enhance our workforce intelligence capabilities.

As part of our team, you’ll collaborate with experienced NLP data scientists and engineers to design, develop, and optimize algorithms and models that power next-generation workforce solutions. This is a unique opportunity to build your career in AI and NLP while contributing to impactful, real-world applications.

If you're eager to work on cutting-edge technology that is reshaping workforce planning and decision-making, we’d love to hear from you. Join us and help redefine how organizations understand and manage talent.

Major Responsibilities:
• Design and develop advanced NLP algorithms and models tailored specifically to workforce intelligence applications, such as job postings and professional profiles analysis.
• Analyze and preprocess large-scale multilingual text data, ensuring accuracy, consistency, and readiness for advanced modeling and real-world applications.
• Conduct rigorous experimentation and validation of NLP models using robust statistical methodologies and relevant evaluation metrics, continuously improving model performance and reliability.
• Deploy, monitor, and maintain NLP-driven applications in production, collaborating closely with engineering and product teams to ensure optimal scalability and efficiency.
• Stay abreast of the latest NLP research and methodologies, proactively integrating innovative techniques into the team’s workflows to maintain cutting-edge capabilities.
• Create comprehensive documentation and guidelines for NLP processes, algorithms, and models, promoting transparency and efficient knowledge sharing within the team.
• Effectively communicate technical insights and results to diverse stakeholders, facilitating informed decision-making and alignment across cross-functional teams.

Education and Experience:
• Bachelor’s or Master’s in Computer Science, Data Science, Machine Learning, AI, or a related field
• 3+ years of hands-on experience in NLP, machine learning, or applied data science; workforce analytics experience strongly preferred
• Solid foundation in NLP, including transformer-based models, LLMs, and knowledge graphs
• Experience with prompt engineering, few-/zero-shot learning, and RAG for tailored NLP applications
• Proficient in parameter-efficient fine-tuning (e.g., LoRA, QLoRA, adapters) to optimize performance and efficiency
• Strong Python skills; experience with Hugging Face Transformers, LangChain, LlamaIndex, and vector databases (e.g., Pinecone, Chroma)
• Knowledge of model optimization techniques like quantization, distillation, and pruning
• Familiar with responsible AI practices, including bias mitigation and model transparency
• Experience with GPU acceleration and distributed training for scalable NLP solutions
• Strong analytical and problem-solving skills; able to align NLP models to business needs
• Excellent communication and collaboration skills in cross-functional environments

Lightcast is a global leader in labor market insights with headquarters in Moscow (ID) with offices in the United Kingdom, Europe, and India. We work with partners across six continents to help drive economic prosperity and mobility by providing the insights needed to build and develop our people, our institutions and companies, and our communities.

Lightcast is proud to be an equal opportunity workplace and is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. Lightcast has always been, and always will be, committed to diversity, equity and inclusion. We seek dynamic professionals from all backgrounds to join our teams, and we encourage our employees to bring their authentic, original, and best selves to work.

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