Data Scientist, NLP & Language Models (Remote - US)

Remote, USA Full-time
This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Data Scientist, NLP & Language Models in the United States. This role offers an exciting opportunity to work with large-scale healthcare data, developing NLP and machine learning models that directly impact products used across multiple industries. You will contribute to the full model lifecycle, from data preprocessing and research to deployment and monitoring, collaborating closely with Data Scientists, ML Engineers, and Product teams. The position involves designing models for tasks like classification, named-entity recognition, and dependency parsing while optimizing model performance in production pipelines. You will help define performance metrics, improve data quality, and implement continuous learning systems. This role requires both technical expertise and a collaborative mindset to translate complex data challenges into actionable solutions. It is ideal for someone who thrives in a fast-paced, innovation-driven environment. Accountabilities: • Develop and deploy NLP and language model solutions for diverse healthcare and business applications. • Perform error analysis, data cleaning, and preprocessing to improve model accuracy and reliability. • Collaborate with cross-functional teams to define product requirements and key performance metrics for models. • Optimize machine learning models and integrate them into production-ready pipelines. • Contribute to the development roadmap by recommending enhancements and new capabilities. • Design systems for continuous learning, active learning, and long-term improvement of models and data quality. Requirements: • Advanced degree in Computer Science, Data Science, Statistics, or a related field, or equivalent work experience. • 4+ years of professional experience in data science and machine learning in an industry setting. • 4+ years of hands-on experience with Python. • Proven experience designing and building NLP models for tasks such as classification, named-entity recognition, and dependency parsing. • Proficiency with standard data analysis toolkits, including SQL, NumPy, and Pandas. • Experience with deep learning frameworks such as PyTorch (preferred) or TensorFlow. • Strong teamwork skills with the ability to contribute to decisions in ambiguous situations. • Effective time management and prioritization skills to meet tight deadlines. • Initiative and ability to independently explore and research novel topics in NLP and AI. Benefits: • Competitive total cash compensation: $136,000 – $170,000 USD. • Opportunity to work with large-scale, impactful datasets in a high-growth environment. • Inclusive, values-driven culture that supports diversity and professional growth. • Health and safety compliance support, including assistance with vaccinations and screenings where applicable. • Access to learning and development opportunities to grow skills and advance your career. Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching. When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly. Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience, and achievements. It compares your profile to the job’s core requirements and past success factors to determine your match score. Based on this analysis, we automatically shortlist the 3 candidates with the highest match to the role. When necessary, our human team may perform an additional manual review to ensure no strong profile is missed. The process is transparent, skills-based, and free of bias — focusing solely on your fit for the role. Once the shortlist is completed, we share it directly with the company that owns the job opening. The final decision and next steps (such as interviews or additional assessments) are then made by their internal hiring team. Thank you for your interest! #LI-CL1
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