NLP Data Scientist

Vintti is a forward-thinking staffing agency at the forefront of global talent solutions. We specialize in connecting US-based SMBs, startups, and firms with highly skilled professionals from Latin America. Our innovative approach breaks down geographical barriers, allowing businesses to tap into a rich pool of diverse talent while offering Latin American professionals access to exciting international career opportunities. Vintti builds bridges across continents, fostering cultural exchange and driving business growth through strategic staffing solutions.

An NLP Data Scientist harnesses the power of natural language processing to analyze and interpret vast amounts of unstructured text data. By developing sophisticated algorithms and leveraging machine learning techniques, they transform linguistic data into actionable insights that drive business decisions. Their role involves everything from pre-processing raw text and feature extraction to model building and fine-tuning. Working across diverse data sources, including social media, customer reviews, and more, NLP Data Scientists enable organizations to comprehend and respond to human language effectively, enhancing communication and operational efficiency.

- Master's or Ph.D. in Computer Science, Data Science, Statistics, Applied Mathematics, or a related field.
- 3+ years of hands-on experience in natural language processing (NLP) or related fields.
- Strong proficiency in programming languages such as Python or R.
- Experience with NLP libraries and frameworks such as NLTK, SpaCy, TensorFlow, PyTorch, or Hugging Face.
- Proficient in machine learning techniques and algorithms for NLP tasks, including text classification, named entity recognition, sentiment analysis, and machine translation.
- Experience with data preprocessing techniques for large text datasets.
- Demonstrated ability in exploratory data analysis and data visualization.
- Strong understanding of language models and experience in training and fine-tuning them.
- Familiarity with cloud platforms and services such as AWS, GCP, or Azure.
- Knowledge of database systems and query languages such as SQL.
- Excellent problem-solving and analytical skills.
- Good communication skills, both written and verbal, particularly the ability to convey complex technical concepts to non-technical stakeholders.
- Proven track record of collaborating with cross-functional teams.
- Knowledge of best practices in software development, including version control, code reviews, and continuous integration.
- Demonstrated ability to write and maintain technical documentation.
- Strong organizational and time-management skills with the ability to manage multiple projects simultaneously.
- Experience in mentoring or providing guidance to junior data scientists or interns.
- Knowledge of data security and privacy considerations in NLP projects.
- Ability to stay updated with the latest advancements and research in NLP and machine learning fields.

- Design, implement, and evaluate NLP models and algorithms.
- Clean, preprocess, and curate large text datasets.
- Develop and maintain NLP pipelines for data processing and analysis.
- Perform feature engineering on textual data to enhance model performance.
- Conduct exploratory data analysis and visualization to extract insights.
- Train and fine-tune language models using frameworks such as TensorFlow, PyTorch, or Hugging Face.
- Implement and optimize machine learning algorithms for text classification, named entity recognition, sentiment analysis, and machine translation.
- Collaborate with cross-functional teams to integrate NLP solutions into production systems.
- Monitor and evaluate the performance of deployed NLP models.
- Research and stay updated on the latest advancements in NLP and machine learning.
- Prepare technical documentation and reports to share findings and methodologies.
- Conduct code reviews and provide feedback to peers.
- Develop and execute tests to validate NLP model performance and reliability.
- Debug and resolve issues related to model performance, scalability, or data quality.
- Communicate complex technical concepts and project status to non-technical stakeholders.
- Design and conduct experiments to explore new approaches or improve existing NLP methods.
- Contribute to the development of internal NLP libraries and tools.
- Participate in team meetings, brainstorming sessions, and knowledge-sharing initiatives.
- Identify and mitigate potential risks associated with NLP projects and data security.
- Provide mentorship and guidance to junior data scientists and interns on NLP-related projects.

The ideal candidate for the NLP Data Scientist role holds a Master's or Ph.D. in Computer Science, Data Science, Statistics, Applied Mathematics, or a related field, with over three years of hands-on experience in natural language processing. This individual possesses a deep proficiency in programming languages like Python or R and is adept in utilizing NLP libraries and frameworks such as NLTK, SpaCy, TensorFlow, PyTorch, or Hugging Face. They demonstrate a robust understanding of machine learning techniques and algorithms, particularly for text classification, named entity recognition, sentiment analysis, and machine translation. Known for their meticulous attention to detail and excellent problem-solving skills, the candidate excels in data preprocessing and exploratory data analysis, showing a strong command over data visualization and feature engineering. Experience with cloud platforms like AWS, GCP, or Azure, and proficiency in SQL database queries further bolster their technical prowess. The ideal candidate exhibits a collaborative spirit, thriving in cross-functional team environments and effectively communicating complex technical concepts to non-technical stakeholders. A proactive and curious approach to staying abreast of the latest advancements in NLP and machine learning is coupled with exceptional organizational and time-management abilities, enabling them to handle multiple projects concurrently. Their commitment to high-quality code standards, coupled with experience in best software development practices, sets them apart. An effective mentor, they exhibit a passion for guiding and supporting junior team members, and they prioritize ethical considerations around data security and privacy. Agile and adaptable, the ideal candidate is resilient in troubleshooting challenging problems, consistently driving impactful outcomes with a results-oriented mindset.

- Design, implement, and evaluate natural language processing (NLP) models and algorithms.
- Clean, preprocess, and curate large text datasets for NLP projects.
- Develop and maintain NLP pipelines for data processing and analysis.
- Perform feature engineering on textual data to enhance model performance.
- Conduct exploratory data analysis and visualization to extract insights from text data.
- Train and fine-tune language models using frameworks such as TensorFlow, PyTorch, or Hugging Face.
- Implement and optimize machine learning algorithms for tasks such as text classification, named entity recognition, sentiment analysis, and machine translation.
- Collaborate with cross-functional teams to integrate NLP solutions into production systems.
- Monitor and evaluate the performance of deployed NLP models to ensure robustness and accuracy.
- Research and stay updated on the latest advancements in NLP and machine learning technologies.
- Prepare technical documentation and reports to share findings and methodologies.
- Conduct code reviews and provide feedback to peers to ensure high-quality code standards.
- Develop and execute tests to validate the performance and reliability of NLP models.
- Debug and resolve issues related to model performance, scalability, or data quality.
- Communicate complex technical concepts and project status to non-technical stakeholders.
- Design and conduct experiments to explore new approaches or improve existing NLP methods.
- Contribute to the development of internal NLP libraries and tools for data scientists.
- Participate in team meetings, brainstorming sessions, and knowledge-sharing initiatives.
- Identify and mitigate potential risks associated with NLP projects and data security.
- Provide mentorship and guidance to junior data scientists and interns on NLP-related projects.

- Strong analytical and problem-solving skills
- Deep passion for natural language processing and machine learning
- Curiosity and eagerness to stay updated with cutting-edge NLP research
- Excellent attention to detail and thoroughness in work
- Ability to work independently with minimal supervision
- Collaborative mindset and ability to work well in cross-functional teams
- Proactive in identifying and addressing potential issues or improvements
- Effective communicator with the ability to explain complex technical concepts clearly
- Strong organizational and time-management skills
- Agile and adaptable to fast-paced and evolving project requirements
- Enthusiastic about mentoring and guiding junior team members
- High degree of intellectual curiosity and a willingness to experiment with new methods
- Commitment to high-quality code standards and best practices
- Strong ethical considerations, especially regarding data security and privacy
- Resilient and persistent in troubleshooting and debugging challenging problems
- A results-driven approach with a focus on achieving impactful outcomes

- Competitive salary range
- Comprehensive health insurance (medical, dental, vision)
- Retirement savings plan with company match
- Paid time off (vacation, sick days, personal days)
- Parental leave
- Flexible work hours and remote work options
- Professional development budget for conferences, courses, and certifications
- Access to company-sponsored wellness programs (gym memberships, mental health resources)
- Annual performance bonuses and merit-based raises
- Stock options or equity plans
- Generous relocation assistance if applicable
- Company-sponsored social events and team-building activities
- Subsidized commuter benefits
- Ergonomic workstations and modern office facilities
- Access to the latest tools and technologies for NLP research and development
- Opportunity to work on cutting-edge NLP projects and collaborate with leading experts in the field
- Regular hackathons and innovation sprints
- Employee assistance programs (EAP) for personal and professional support
- Internal mentorship programs and career advancement opportunities
- Inclusive and diverse work environment
- Supportive company culture that values work-life balance