Data Scientist (NLP)

Vintti specializes in providing US companies with a financial edge through smart staffing solutions. We bridge the gap between American businesses and Latin American talent, offering access to a vast pool of skilled professionals at competitive rates. This approach enables our clients to scale their operations more efficiently, reduce hiring costs, and invest in growth opportunities without compromising on quality.

A Data Scientist specializing in Natural Language Processing (NLP) leverages advanced algorithms and machine learning techniques to analyze, interpret, and derive insights from human language data. This role involves designing and implementing models to process text and speech, enabling applications like sentiment analysis, language translation, and chatbots. By extracting meaningful patterns and trends from unstructured data, these experts help businesses enhance decision-making, optimize customer interactions, and drive innovation in various fields such as healthcare, finance, and technology. This position requires a combination of technical expertise, analytical skills, and a deep understanding of linguistic nuances.

- Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field.
- Proven experience as a Data Scientist, preferably with a focus on NLP.
- Strong programming skills in Python; experience with NLP libraries and frameworks such as NLTK, SpaCy, TextBlob, TensorFlow, PyTorch, and Hugging Face is essential.
- Experience with machine learning algorithms and statistical methods.
- Familiarity with pre-trained language models such as BERT, GPT-3, and transformers.
- Proficiency in text preprocessing techniques including tokenization, part-of-speech tagging, lemmatization, stemming, and named entity recognition.
- Hands-on experience with data manipulation and data cleaning.
- Solid understanding of various NLP tasks such as sentiment analysis, text classification, and entity recognition.
- Ability to develop and optimize NLP models for high accuracy and efficiency.
- Experience with model deployment and monitoring in a production environment.
- Capable of designing and running experiments to evaluate model performance.
- Strong problem-solving skills and the ability to troubleshoot and debug NLP models.
- Excellent communication skills, both verbal and written, to effectively convey complex technical concepts to non-technical stakeholders.
- Ability to work within a cross-functional team environment.
- Demonstrated ability to keep up-to-date with the latest developments in NLP and continuous learning.
- Familiarity with large-scale data processing frameworks like Spark is a plus.
- Experience with cloud platforms such as AWS, Google Cloud Platform, or Azure is preferred.
- Strong analytical and critical thinking skills, with attention to detail.
- Good understanding of version control systems, such as Git.
- Ability to manage multiple projects and meet deadlines in a fast-paced environment.

- Analyze and interpret large datasets using NLP techniques.
- Develop and implement NLP models for various text processing tasks.
- Optimize models and algorithms for improved performance.
- Preprocess and clean text data effectively.
- Collaborate with engineers, product managers, and stakeholders to meet business needs.
- Design and conduct experiments to validate model performance.
- Utilize machine learning frameworks to build NLP models.
- Fine-tune pre-trained language models for application-specific tasks.
- Monitor deployed models for accuracy and efficiency.
- Stay updated with industry trends and implement new NLP techniques.
- Communicate findings through visualizations, reports, and presentations.
- Collaborate on building and maintaining data pipelines.
- Perform error analysis to improve model robustness.
- Document processes and methodologies for knowledge sharing.
- Participate in code reviews to enhance the quality of code.
- Conduct literature reviews and research for innovative NLP solutions.

The ideal candidate for the Data Scientist (NLP) role is a proactive and self-motivated professional with a robust background in computer science, data science, or a related field, holding at least a Bachelor's degree, though a Master’s is preferred. They possess a profound passion for natural language processing, demonstrated by substantial hands-on experience with NLP libraries and frameworks such as NLTK, SpaCy, TensorFlow, PyTorch, and Hugging Face. They exhibit a strong command of Python programming and are adept at implementing and fine-tuning NLP models like BERT and GPT-3 for diverse tasks, from text classification to sentiment analysis. Their proficiency encompasses advanced text preprocessing techniques and data manipulation, coupled with a proven ability to develop, optimize, and deploy models in production while maintaining high accuracy and efficiency. The candidate is an analytical thinker with excellent problem-solving skills, capable of designing experiments and interpreting large datasets to extract actionable insights. They are adept at collaborating within cross-functional teams, communicating complex technical concepts clearly to both technical and non-technical stakeholders. Their drive for continuous learning ensures they stay abreast of the latest NLP advancements. With solid experience in cloud platforms like AWS or Google Cloud, familiarity with large-scale data processing frameworks like Spark, and proficiency in version control systems such as Git, they manage multiple projects efficiently in a dynamic environment. Attention to detail, strong organizational skills, and a user-centric approach to solution development are hallmarks of their work ethic. Equipped with resilience, creativity, and a high level of integrity, they approach setbacks constructively, embodying a curiosity-driven mindset and a keen sense of accountability that makes them an exceptional fit for this role.

- Analyze large datasets to extract meaningful patterns and insights using natural language processing (NLP) techniques.
- Develop, implement, and optimize NLP models and algorithms for tasks such as text classification, entity recognition, sentiment analysis, and language translation.
- Preprocess and clean text data, including tokenization, part-of-speech tagging, and lemmatization.
- Collaborate with cross-functional teams, including engineers, product managers, and stakeholders, to understand business requirements and deliver data-driven solutions.
- Design and execute experiments to test and validate model performance and effectiveness.
- Utilize machine learning libraries and frameworks such as TensorFlow, PyTorch, and Hugging Face to build and deploy NLP models.
- Fine-tune pre-trained language models (e.g., BERT, GPT-3) for specific application needs.
- Monitor and maintain the performance of deployed models, ensuring they achieve desired accuracy levels and perform efficiently in production.
- Explore and implement new NLP techniques and technologies to stay up-to-date with industry trends and advancements.
- Communicate findings and results through visualizations, reports, and presentations to technical and non-technical audiences.
- Collaborate on data pipeline development to ensure efficient data flow between storage, processing, and analysis stages.
- Perform error analysis to identify challenges and improve model accuracy and robustness.
- Document processes, methodologies, and key findings for knowledge sharing and reproducibility.
- Participate in code reviews and provide constructive feedback to enhance the overall code quality.
- Conduct literature reviews and research to explore potential improvements and innovative solutions in the field of NLP.

- Proactive and self-motivated with a strong passion for NLP.
- Detail-oriented with a keen eye for identifying patterns and insights.
- Strong analytical and critical thinking abilities.
- Excellent problem-solving skills with a focus on practical solutions.
- Adaptable and flexible in a fast-paced, dynamic environment.
- Strong collaboration and communication skills.
- Ability to explain complex technical concepts in simple terms.
- Innovative mindset with a continuous learning attitude.
- Efficient time-management and organizational skills.
- Strong sense of accountability and ownership of projects.
- Curiosity-driven with an eagerness to explore new technologies and techniques.
- Resilient and able to handle setbacks constructively.
- Empathetic with a user-centric approach to solutions.
- Team player with the ability to work effectively in cross-functional teams.
- High level of integrity and ethical conduct.

- Competitive salary range based on experience and qualifications.
- Comprehensive health, dental, and vision insurance plans.
- Flexible work hours and remote work options.
- Generous paid time off (PTO) and holidays.
- Professional development opportunities and access to industry conferences and workshops.
- Retirement savings plan with employer matching contributions.
- Employee wellness programs, including mental health resources and fitness memberships.
- Stock options or equity grants for long-term incentives.
- Annual performance bonuses based on individual and company performance.
- Opportunities for career advancement and role-specific training.
- Access to cutting-edge technology and tools for NLP research and development.
- Collaborative and inclusive work culture that values diversity.
- Regular team-building events and social activities.
- Tuition reimbursement for continuing education and advanced degrees.
- Childcare support and family leave policies.
- Ergonomic workstations and modern office facilities.
- Employee referral program with bonus incentives.
- Life and disability insurance coverage.
- Well-stocked kitchen with snacks and beverages.