Job Title : Associate Director, Data Scientist
Location : Remote
Key Responsibilities :
- Data Analysis and Preprocessing : Analyze and preprocess diverse datasets relevant to the mortgage industry, ensuring data quality and relevance for model training.
- Model Development and Fine-Tuning : Research and implement state-of-the-art NLP models, focusing on pre-training as well instruction tuning pre-trained LLMs for domain-specific applications. Utilize techniques like RLHF to improve model alignment with human preferences and enhance decision-making capabilities.
- Algorithm Implementation : Develop and optimize machine learning algorithms to enhance model performance, accuracy, and efficiency. Experiment with different architectures and open-source models to identify the best fit for project requirements.
- Collaboration : Work with domain experts to incorporate industry knowledge into model development, ensuring outputs are relevant and actionable.
- Experimentation : Conduct experiments to validate model hypotheses, analyze results, and iterate on model improvements.
- Documentation : Maintain comprehensive documentation of methodologies, experiments, and results to support transparency and reproducibility.
- Ethics and Bias Mitigation : Ensure responsible AI practices are followed by identifying potential biases in data and models, implementing strategies to mitigate them.
Required Skills :
Technical Expertise : Strong background in machine learning, deep learning, and NLP. Proficiency in Python and experience with ML frameworks such as TensorFlow or PyTorch.NLP Knowledge : Experience with NLP frameworks and libraries (e.g., Hugging Face Transformers) for developing language models.Data Handling : Proficiency in handling large datasets, feature engineering, and statistical analysis.Problem Solving : Strong analytical skills with the ability to solve complex problems using data-driven approaches.Communication : Excellent communication skills to effectively collaborate with technical teams and non-technical stakeholders.Preferred Qualifications :
Educational Background : Master’s or Ph.D. in Data Science, Computer Science, Statistics, or a related field.Cloud Computing : Familiarity with cloud platforms (e.g., AWS, Azure) for scalable computing solutions.Ethics Awareness : Understanding of ethical considerations in AI development, including bias detection and mitigation.