Mortgage Industry Data Science Lead

2 days ago


Vijayawada, Andhra Pradesh, India beBeeData Full time ₹ 50,000 - ₹ 55,000
Job Overview

We are seeking an experienced Senior Lead to spearhead our data science initiatives in the mortgage industry. The ideal candidate will possess a strong background in machine learning, deep learning, and NLP.

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 mortgage-specific applications.
  • Algorithm Implementation: Develop and optimize machine learning algorithms to enhance model performance, accuracy, and efficiency.
  • 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.

Requirements:

  • 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.


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