Language Data Scientist - Saskatoon, SK

Job Title: Language Data Scientist · Location: Remote within Canada (excluding Quebec) · Employment Type: Full-Time (40 hours per week) Fixed-Term · Who we are: · Innodata (NASDAQ: INOD) is a leading data engineering company. With more than 2,000 customers and operations in 13 ci ...

Job description

Job Title: Language Data Scientist

Location: Remote within Canada (excluding Quebec)

Employment Type: Full-Time (40 hours per week) Fixed-Term

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 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 7,000 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:

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.

Key Responsibilities:

• 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.

Qualifications:

• 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 language and its relationship with culture
• Ability to identify ambiguity and subjectivity in language
• Ability to work with multi-lingual and multi-modal projects
• Language and language data expertise:
• Quantitative Analysis Skills: Advanced knowledge of statistics, metrics (e.g. f1 score, inter-rater reliability metrics), and data analysis methods such as sampling.
• Technical skills:
• 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)
• Data processing:
• 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.

Preferred Qualifications:

• Conducting research to stay up-to-date with the latest advancements in generative AI, machine learning, and deep learning techniques
• Knowledge of optimizing existing generative AI models for improved performance, scalability, and efficiency
• Experience of developing and maintaining ML/AI pipelines, including data preprocessing, feature extraction, model training, and evaluation
• Model Fine-Tuning: Knowledge of Fine-tuning pre-trained models to adapt them to specific tasks and datasets, improving their performance and relevance
• Developing clear and concise documentation, including technical specifications, user guides, and presentations, to communicate complex AI concepts to both technical and nontechnical stakeholders
• Contributing to establishing best practices and standards for generative AI development with customers and within the organization
• Providing technical mentorship and guidance to junior team members
• Understanding of techniques such as GPT, VAE, and GANs

Salary Range: Up to $120k CAD

Rates at Innodata vary depending on a wide array of factors, which may include but are not limited to the role, skill set, educational background and geographic location.