Senior Data Scientist

Description

We are currently seeking a talented Sr. Data Scientist with experience in Machine Learning, Deep Learning, and Natural Language Processing, coupled with robust coding abilities in Python.

Responsibilities

• Conduct exploratory data analysis to identify trends, patterns, and insights from various data sources.
• Develop and deploy cutting-edge NLP models to extract insights from unstructured data sources.
• Design and implement robust search algorithms and recommendation systems to enhance user experience and engagement.
• Collaborate with cross-functional teams (Business, Product, DevOps, and Engineering) to gather requirements, analyze data, and integrate models into production systems.
• Stay updated with the latest advancements in NLP, machine learning, and recommendation systems to drive innovation.
• Effectively communicate findings and results to both technical and non-technical stakeholders.
• Ensure data security, quality, and compliance with relevant regulations.
• Provide mentorship and guidance to junior team members.
• Participate in the evaluation and selection of appropriate tools, technologies, and platforms for data science projects.

Skills and Qualifications

Expertise in Generative AI and Natural Language Processing/Generation, with a focus on vector embeddings.

RAG, Deep Learning, Vector database, transformer, LLM, LLM finetuning

Experience with building and deploying large scale ML models in production environments.

Proficiency in text processing and a solid grasp of Probability & Statistics are essential.

Strong programming skills in Python for data analysis and model development.

Solid understanding and practical experience with machine learning techniques and libraries such as TensorFlow, PyTorch, and scikit-learn.

Experience with both SQL (MySQL, PostgreSQL, BigQuery, Redshift, etc.) and No-SQL (MongoDB, Aerospike, etc.) databases.

Sound grasp of statistical concepts, hypothesis testing, and experimental design.

Familiarity with deep learning frameworks and algorithms including Facebook's DeepText, FastText, RoBERTa, Word2Vec, RNN, CNN, R-CNN, LSTM, XGBoost, GRU,

Sequence-to-Sequence, and Transformer-based architectures (e.g., Decoder-Decoder, Encoder-Decoder, etc.).

Desirable experience with cloud platforms such as Azure, AWS, or Google Cloud, and Vector DBs like Milvus, Weaviate, and Qdrant.

Good to have knowledge of Large Language Models (LLMs) and experience with fine-tuning them for specific tasks.