Binance Accelerator Program - Data Scientist (NLP)

Binance is the global blockchain company behind the world’s largest digital asset exchange by trading volume and users, serving a greater mission to accelerate cryptocurrency adoption and increase the freedom of money.

Are you looking to be a part of the most influential company in the blockchain industry and contribute to the crypto-currency revolution that is changing the world?

About Binance Accelerator Program Binance Accelerator Program is a concise fixed-term program designed for Early Career Talent to have an immersive experience in the rapidly expanding Web3 space. You will be given the opportunity to experience life at Binance and understand what goes on behind the scenes of the worlds’ leading blockchain ecosystem. Alongside your job, there will also be a focus on networking and development, which will expand your professional network and build transferable skills to propel you forward in your career. Learn about BAP Program HERE Who may apply

Current university students

Responsibilities：

• Utilize NLP techniques to preprocess, analyze, and extract insights from large textual datasets. Develop and implement NLP models to derive actionable insights and enhance business decision-making processes.
• Design, develop, and evaluate complex data models to support statistical analysis, machine learning, and other data-driven tasks. Ensure data models are robust, scalable, and optimized for performance.
• Perform data cleaning, transformation, and preprocessing to create high-quality datasets for analysis and modeling.
• Conduct exploratory data analysis to uncover patterns, trends, and relationships within the data. Generate visualizations and summaries to communicate findings to stakeholders.
• Develop and apply feature engineering techniques to create meaningful features that improve the performance of models. This includes deriving new features from raw data, selecting relevant features, and transforming existing features.

Requirements:

• Proficient in designing, developing, and evaluating complex data models. Familiarity with statistical analysis and machine learning frameworks.
• Deep understanding of modern machine learning techniques and mathematical underpinning, such as classifications, neural networks, hyperparameter optimization, etc.
• Strong knowledge and experience in NLP techniques and tools for analyzing and extracting insights from textual data.
• Solid understanding and practical experience with deep learning architectures, including transformer models (e.g., BERT, GPT). Ability to implement and optimize these models for various tasks.
• Proficiency in programming languages such as Python, R, or similar. Experience with libraries and frameworks such as TensorFlow, PyTorch, Keras, and Scikit-learn.
• Demonstrated experience in handling severely imbalanced datasets. Knowledge of techniques and strategies to address imbalances in data.
• Holds a Master's degree or higher in Computer Science, Data Science, Statistics, Mathematics, Computational Linguistics, or a related field. Current Master's or Ph.D. students are welcome to apply.