Innodata – Language Data Scientist

Who we are:

Innodata (NASDAQ: INOD) is a leading data engineering company. With more than 2,000 customers and operations in 13 cities around the world, we are the AI technology solutions provider‑of‑choice to 4 out of 5 of the world’s biggest technology companies, as well as leading companies across financial services, insurance, technology, law, and medicine.

By combining advanced machine learning and artificial intelligence (ML/AI) technologies, a global workforce of subject matter experts, and a high‑security infrastructure, we’re helping usher in the promise of clean and optimized digital data to all industries. Innodata offers a powerful combination of both digital data solutions and easy‑to‑use, high‑quality platforms.

Our global workforce includes over 3,000 employees in the United States, Canada, United Kingdom, the Philippines, India, Sri Lanka, Israel and Germany. We’re poised for a period of explosive growth over the next few years.

Innodata is building a team of Language Data Scientists and Gen AI experts to help our customers advance GenAI applications. You will work hands‑on with multi‑modal and multi‑lingual datasets and collaborate with cross‑functional partners. You will use your experience with human and synthetic data workflows to drive innovation and continuous improvement. The ideal candidate must have the right mix of skills in (computational) linguistics and human evaluation tasks, data science, and data engineering.

You have at least 3 years of relevant experience with data creation, curation and analysis for GenAI applications (e.g. RAG, Agents, complex reasoning). You are an expert in designing collection, evaluation and quality assurance processes, using human‑in‑the‑loop and synthetic techniques. You bring a wealth of expertise in language, culture, and multi‑lingual projects. You are experienced in analyzing data with advanced statistical tools and driving success through process excellence.

Your understanding of machine learning, Large Language Models (LLMs), and Retrieval‑Augmented Generation (RAG) help you tackle challenges with a critical, innovative mindset. You’re also a strong communicator, excelling in cross‑functional collaboration and understanding business needs.

As a Language Data Scientist, you create and own processes for creating, validating and annotating data for use in LLM/ML applications. This can be natural language data or multimodal data including images, video, audio and others. You consult and engage with customers to understand their business goals and design processes to meet them. You generate insights about the client’s processes and products to drive improvement and innovation.

You advise and support business unit heads on engaging with customers to understand the upstream activities that would be performed using Innodata Inc services.

• 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.
• Knowledge of how components of GenAI products or services combine to work
• Collaborating with cross‑functional teams to define AI project requirements and objectives, ensuring alignment with overall business goals
• MA in (computational) linguistics, data science, computer science (AI / ML / NLU), quantitative social sciences or a related scientific / quantitative field, PhD strongly preferred
• Language and language data expertise:
  Extensive experience working with human language data and designing human evaluation tasks, including multi‑phase and complex workflows.
  • Deep understanding of…