Sr. Data Scientist

We are seeking a talented and experienced Senior Data Scientist to join our team and lead the development of AI-powered solutions for business efficiencies. As a Senior Data Scientist, you will collaborate with cross-functional teams to understand business requirements, design and implement advanced machine learning models, and deliver a cutting-edge solution that transforms unstructured text data into actionable insights.

 

Responsibilities:

1. Co-lead the end-to-end development of AI-powered solutions, from data preprocessing to model deployment.
2. Collaborate with stakeholders to understand business requirements and translate them into technical specifications.
3. Design and implement state-of-the-art natural language processing (NLP) models and algorithms to extract meaningful information from unstructured text data.
4. Develop data pipelines to preprocess and clean large volumes of text data, ensuring data quality and reliability.
5. Train and fine-tune machine learning models using various techniques such as deep learning, transfer learning, and ensemble methods.
6. Evaluate and benchmark different NLP models and techniques to identify the most effective approaches for extracting business insights.
7. Collaborate with software engineers and data engineers to integrate the developed models into scalable, production-ready tools.
8. Conduct thorough testing and validation of the tool to ensure accuracy, performance, and usability.
9. Stay up-to-date with the latest advancements in NLP, text mining, and machine learning techniques, and evaluate their potential for enhancing tools’ capabilities.
10. Provide technical guidance and mentorship to team members, fostering a collaborative and innovative work environment.

 

Qualifications:

1. Bachelor's or Master's degree in Computer Science, Data Science, or a related field.
2. Extensive experience in developing and deploying machine learning models for natural language processing tasks.
3. Strong proficiency in programming languages such as Python, with experience in relevant libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
4. Solid understanding of NLP techniques, including text classification, named entity recognition, sentiment analysis, and topic modeling.
5. Experience with deep learning architectures for NLP, such as recurrent neural networks (RNNs), transformers, and convolutional neural networks (CNNs).
6. Proficiency in data preprocessing techniques for text data, including tokenization, stemming, and feature engineering.
7. Hands-on experience with large-scale text data processing and storage using tools like Apache Spark and Elasticsearch.
8. Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience deploying machine learning models in a scalable, distributed environment.
9. Strong problem-solving and analytical skills, with the ability to extract meaningful insights from complex text data.
10. Excellent communication skills, with the ability to effectively collaborate with cross-functional teams and present insights to non-technical stakeholders and clients.

 

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Last updated on Oct 26, 2023