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Machine Learning Data Linguist information

What are the key skills and qualifications needed to thrive as a Machine Learning Data Linguist, and why are they important?

To thrive as a Machine Learning Data Linguist, you need expertise in linguistics, data annotation, and a strong understanding of language structures, often supported by a degree in linguistics or computational linguistics. Familiarity with annotation tools, data labeling platforms, and programming languages like Python is typically required. Strong attention to detail, analytical thinking, and clear communication are essential soft skills for accurately interpreting and conveying linguistic phenomena. These skills ensure high-quality language data, which is critical for developing effective and unbiased machine learning models.

What is a Machine Learning Data Linguist?

A Machine Learning Data Linguist is a specialist who works at the intersection of linguistics and artificial intelligence. They are responsible for annotating, curating, and analyzing language data to train and improve machine learning models, especially those focused on natural language processing (NLP). Their work often includes tasks like labeling text, refining speech recognition data, and ensuring that language models understand context, grammar, and cultural nuances. This role is essential in developing accurate and inclusive AI systems that interact with human language.

How does a Machine Learning Data Linguist typically collaborate with engineers and data scientists on projects?

A Machine Learning Data Linguist works closely with engineers and data scientists by providing linguistic insights and ensuring that language data is accurately annotated and interpreted. They often participate in cross-functional meetings to define project goals, clarify annotation guidelines, and review model outputs for linguistic quality. This collaboration helps bridge the gap between technical development and language-specific nuances, leading to more effective and culturally accurate machine learning models. Effective communication and a strong understanding of both linguistic theory and technical requirements are vital in this collaborative environment.
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Machine Learning Data Linguist jobs near you
Machine Learning / Data Scientist

Machine Learning / Data Scientist

Parsons

Washington, DC

$88K - $154K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 22 days ago

Parsons rating

7.9

Company rating: 7.9 out of 10

Based on 45 frontline employees who took The Breakroom Quiz

219th of 442 rated engineering

Job description

In a world of possibilities, pursue one with endless opportunities. Imagine Next!At Parsons, you can imagine a career where you thrive, work with exceptional people, and be yourself. Guided by our leadership vision of valuing people, embracing agility, and fostering growth, we cultivate an innovative culture that empowers you to achieve your full potential. Unleash your talent and redefine what's possible.

Job Description:

We have a career opportunity for a Machine Learning / Data Scientist to develop advanced analytical models and experiments that enhance decision-making, improve forecasting, and uncover insights across mission and support activities. This role would be based in Washington, DC. Would be required to be on-site

This role will support the enablement of machine learning capabilities within our analytics environment, working closely with data analysts, engineers, and program stakeholders.

The Machine Learning / Data Scientist is a hands-on practitioner with strong capabilities in model development, data preparation, and analytical storytelling. This role requires the ability to frame complex problems, select appropriate modeling approaches, implement and validate models, and communicate results in accessible terms to non-technical audiences.

Key Responsibilities:

  • Design and implement machine learning and advanced analytics solutions that address operational, programmatic, or strategic questions.
  • Collaborate with stakeholders to define analytical problems, identify relevant data, and translate business needs into modeling requirements.
  • Prepare and engineer features from multiple data sources, ensuring data quality and suitability for modeling.
  • Develop, train, and validate models (e.g., classification, regression, clustering, forecasting) using appropriate techniques and tools.
  • Evaluate model performance, perform error analysis, and refine approaches to improve accuracy, robustness, and interpretability.
  • Integrate model outputs into dashboards, applications, or automated workflows, in coordination with analytics and development teams.
  • Document modeling approaches, assumptions, and results, and communicate findings through clear narratives and visualizations.
  • Support experimentation and pilot projects that explore new analytical techniques and tools.
  • Contribute to the development of standards and practices for responsible and sustainable use of advanced analytics.

Typical Assignments:

  • Building predictive or prescriptive models that support prioritization of projects, resource allocation, or risk assessment.
  • Conducting exploratory data analysis to identify patterns, anomalies, and opportunities for improved performance.
  • Developing prototypes of ML-enabled features that can be integrated into existing dashboards or applications.
  • Supporting performance management by providing advanced analyses of trends and drivers underlying key metrics.
  • Collaborating with data management staff to ensure datasets are suitable for modeling and reproducible analysis.
  • Preparing technical and non-technical presentations that summarize modeling methods, findings, and implications.

Education and Experience:

  • Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, or a closely related field; a master's degree is preferred but not required, or equivalent work experience.
  • 5+ years of experience in data science, machine learning, or advanced analytics roles.
  • Demonstrated experience developing, validating, and deploying machine learning models using tools such as Python, R, or equivalent.
  • Strong background in statistics, model evaluation, and experimental design.
  • Experience with data preparation, feature engineering, and working with complex, multi-source datasets.
  • Familiarity with integrating model outputs into BI tools or applications (e.g., via APIs, embedded analytics) is preferred.
  • Experience working within mission-oriented or public sector environments (e.g., DHS, DoD) is a plus.

Security Clearance Requirement:

NoneThis position is part of our Critical Infrastructure team.For more than 80 years, our experts have designed and delivered the critical infrastructure that connects and protects communities around the world. We work in collaborative teams, both within the company and with our partners and customers, to plan, design, build, and modernize infrastructure. We take special pride in projects and solutions that improve communities as well as people's quality of life by promoting economic growth, enhancing mobility, and increasing sustainability and resiliency. Powered by our people, we provide the imagination necessary to support our customers' visions-and to help them see what's next!Salary Range: $88,400.00 - $154,700.00We value our employees and want our employees to take care of their overall wellbeing, which is why we offer best-in-class benefits such as medical, dental, vision, paid time off, Employee Stock Ownership Plan (ESOP), 401(k), life insurance, flexible work schedules, and holidays to fit your busy lifestyle!Parsons is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, veteran status or any other protected status.We truly invest and care about our employee's wellbeing and provide endless growth opportunities as the sky is the limit, so aim for the stars! Imagine next and join the Parsons quest-APPLY TODAY!

Parsons is aware of fraudulent recruitment practices. To learn more about recruitment fraud and how to report it, please refer tohttps://www.parsons.com/fraudulent-recruitment/.

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