Senior Data Scientist (Remote from United States)

Jobgether

1d • Remote

About The Position

This role offers the opportunity to influence the quality and effectiveness of AI models by leading the evaluation, curation, and optimization of large-scale datasets. You will design and implement statistical and machine learning methods to ensure datasets are diverse, representative, and high-impact. Collaborating closely with research and engineering teams, you will define data quality standards, develop assessment frameworks, and create tools to automate preprocessing and validation. This position combines hands-on technical work with strategic guidance, allowing you to shape the future of AI model performance. Ideal candidates are independent problem-solvers with strong analytical skills, experience with unstructured datasets, and a passion for data-centric AI research. This is a fully remote role in a fast-paced, collaborative, and high-trust environment.

Requirements

• PhD or equivalent Master’s degree with 4+ years of industry experience in machine learning, computer science, statistics, mathematics, engineering, or a related quantitative field.
• Strong understanding of AI model training pipelines, including data preprocessing and evaluation.
• Experience with large, unstructured datasets, especially text-based data.
• Background in statistical analysis, bias detection, and data validation.
• Proven ability to identify high-impact problems and implement independent solutions.
• Excellent collaboration and communication skills for cross-functional teamwork.

Nice To Haves

• experience with synthetic data generation or augmentation
• open-source contributions
• publications in data-centric AI
• experience developing evaluation frameworks or performance metrics

Responsibilities

• Lead the evaluation, curation, and optimization of large-scale datasets used for AI model training.
• Design and apply statistical and machine learning techniques to filter, enrich, and assess data quality.
• Develop frameworks to measure data diversity, duplication, and informativeness, reducing risks in training datasets.
• Collaborate with model training teams to identify bottlenecks and optimize dataset performance.
• Provide leadership on data quality strategy and define internal best practices.
• Evaluate external datasets for integration, focusing on scalability, quality, and relevance, and develop data scorecards.
• Contribute to the research and development of tools for automated data preprocessing, validation, and enrichment.

Benefits

• Competitive compensation package with performance-based incentives.
• Fully remote and flexible working arrangements.
• Opportunity to work on high-impact AI projects with cutting-edge datasets.
• Collaborative, high-trust culture emphasizing velocity, impact, and experimentation.
• Direct influence on AI model performance and data quality strategy.
• Exposure to advanced research and applied machine learning initiatives.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Ph.D. or professional degree