Statistics Specialist

Overview

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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 an AI technology solutions provider of choice for 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 AI. Innodata offers a powerful combination of both digital data solutions and easy-to-use, high-quality platforms. Our global workforce includes over 5,000 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. About the role: At Innodata, we\'re working with the world\'s largest technology companies on the next generation of generative AI and large language models (LLMs). We are seeking a highly skilled Data Scientist with a Master\'s or PhD in Statistics, Applied Mathematics, or a related quantitative field to join our cutting-edge AI team.

• Contribute to the development, training, and fine-tuning of Large Language Models (LLMs) by applying statistical methods, data analysis, and model evaluation techniques.
• Design and implement statistical frameworks for the preparation, analysis, and quality assessment of large-scale datasets used in training LLMs.
• Perform exploratory data analysis (EDA) to detect biases, data inconsistencies, and anomalies in training corpora.
• Collaborate closely with AI researchers and engineers to develop data annotation guidelines and evaluation protocols.
• Apply advanced statistical methods to assess model outputs and guide iterative training improvements.
• Develop and maintain automated tools for data preprocessing, labeling, sampling, and quality control in LLM pipelines.
• Conduct rigorous hypothesis testing, A/B testing, and performance benchmarking of LLMs across various tasks.
• Interpret model behaviors using statistical insights and provide actionable recommendations for model fine-tuning.
• Document methodologies, maintain reproducible workflows, and contribute to technical publications.

• Master\'s or PhD in Statistics, Applied Mathematics, Data Science, Computer Science (with strong statistics focus), or related quantitative field.
• Strong knowledge of statistical modeling, probability theory, and experimental design.
• Hands-on experience with large-scale datasets, data cleaning, feature engineering, and statistical analysis tools.
• Proficiency in programming languages such as Python, R, or Julia, including libraries like pandas, NumPy, SciPy, scikit-learn, or statsmodels.
• Familiarity with machine learning frameworks (TensorFlow, PyTorch) and understanding of LLM architectures (transformers, attention mechanisms).
• Experience with annotation tools and data labeling processes is a plus.
• Strong analytical thinking, attention to detail, and problem-solving skills.
• Excellent written and verbal communication skills in English.
• As part of the project, you are required to complete the English language assessment.

• The assessment is mandatory and non-billable.

• Seniority level: Entry level
• Employment type: Full-time
• Job function: Research, Analyst, and Information Technology
• Industries: Business Consulting and Services

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