We are looking for a Data Scientist who will work with our product and engineering innovating new techniques for applying Artificial Intelligence, Machine Learning, and data analytics techniques to automate digital accessibility use cases by way of chats, copilots, and any other automation that streamlines making digital properties more accessible.
This role will focus initially on LLMs and will expand over time with knowledge of other AI technologies preferred.
The Data Scientist's responsibilities will include :
- Develop components, services, and modules for document classification, information extraction and interpretation
- Measure, improve, and validate confidence scores through detailed and continuous testing
- Design and implement automated testing and feedback to improve model development, results and information extraction with high confidence
- Collaborate with engineering to understand the costs and support informing cost efficient approaches related to the use cases being solved with ML / AI
- Evaluate emerging tools and methodologies to assess the impact on solution design and implementation
- Identify relevant data sources to mine for business needs, and collect large structured and unstructured datasets and variables;
lead data quality and define procedures to solve quality issues
- Apply predictive modeling and other methods to perform quantitative and qualitative data analysis
- Communicate, document, and collaborate cross-functionally, and work well in a team-oriented environment
- Drive the need for security, privacy, and ethics and make solid recommendations regarding approaches to ensure model outputs are ethical and accurate working with information security
- Work with / within product and engineering teams building solutions that use different AI technologies and data to solve a business need
Required skills and experience :
- Bachelor's Degree or equivalent experience in Data Science, Mathematics, Computer Science or related field
- 3+ years of proven experience in a professional work environment as a data-scientist
- Experience using ML frameworks and programming with tools such as R, Python, SQL or similar
- Experience with machine learning, LLMs, Big Data, and NoSQL
- Experience and demonstrable knowledge of Deep Learning concepts
- Understanding of probability and statistics and machine learning concepts such as precision, recall, optimization, hyperparameter tuning, overfitting, and interpretability
- Experience in applying standard implementations of machine learning algorithms effectively by choosing a suitable model such as a decision tree, knn, neural net,
or an ensemble of multiple models
- Understanding of how components and processes work together and communicate with each other using library calls, REST APIs queueing / messaging systems and database queries
- Understanding of system design to avoid bottlenecks and let your algorithms scale well with increasing volumes of data
- Understanding of LLMs and how to use them to preprocess data for us in the LLM (auto-evaluate)
- Knowledge of computer vision AI technologies preferred, but not essential
- Determined and self-guided in a dynamic environment
