Senior Language Data Scientist

Role Overview

• You can lead long-term projects with high complexity and ambiguity from first discussion with the client to completion
• Design/improve workflows to create data for AI/ML training and evaluation. Includes human annotation and data-collection workflows, as well as synthetic ones
• Dive deep into existing workflows and processes to gather data and insights, make recommendations, and drive improvement through innovation and cross-functional collaboration with customers
• Critically assess annotation tooling and workflows
• Quantitatively analyze large datasets, perform statistical analysis, calculate metrics, and make recommendations to improve accuracy and performance
• Work closely with client stakeholders on understanding goals, gathering requirements, proposing solutions, and executing them.
• Set an ambitious research agenda for improving our products and services
• Contribute to establishing best practices and standards for generative AI development with customers and within the organization

Requirements

• MA in (computational) linguistics, data science, computer science (AI / ML / NLU), quantitative social sciences or a related scientific / quantitative field, PhD strongly preferred
• Ability to collaborate directly with technical stakeholders including senior project managers, data engineers, and research scientists.
• Collaborating with cross-functional teams to define AI project requirements and objectives, ensuring alignment with overall business goals
• Design efficient data strategies for complex long-term projects, potentially involving multiple teams and workflows.
• Knowledge of how components of GenAI products or services combine to work
• Developing clear and concise documentation, including technical specifications, user guides, and presentations, to communicate complex AI concepts to both technical and nontechnical stakeholders
• Familiarity with GenAI technologies that enables you to improve existing processes to handle future challenges.
• Extensive experience working with human language data and designing human evaluation tasks, including multi-phase and complex workflows.
• Deep understanding of language and its relationship with culture
• Ability to identify ambiguity and subjectivity in language
• Ability to work with multi-lingual and multi-modal projects
• Advanced knowledge of statistics, metrics (e.g. f1 score, inter-rater reliability metrics), and data analysis methods such as sampling.
• Experience with Natural Language Processing (NLP) techniques and tools, such as SpaCy, NLTK, or Hugging Face.
• Proficiency in Python to handle / transform large datasets (e.g. pre
• and postprocessing data, pandas) perform quantitative analyses visualize data (for example matplotlib, seaborn)
• Deep understanding of data pipelines to support ML and NLP workflows,
• Knowledge of efficient data collection, transformation, and storage
• Knowledge of data structures, algorithms, and data engineering principles
• Excellent interpersonal skills for effective cross-functional stakeholder engagement
• Excellent problem-solving skills, with the ability to think critically and creatively to develop innovative AI solutions
• Ability to work independently and collaborate as part of a team
• Adaptable to changing technologies and methodologies
• Ability to translate experience, research and development information to understand client products and services.

Tech Stack

• Pandas
• Python

Benefits

• Providing technical mentorship and guidance to junior team members
• Professional development opportunities