Text-Data Data Scientist Job Description (JD)
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An Text-Data Data Scientist Job Description (JD) is a data scientist job description for NLP data scientist roles (who focus on analyzing text and speech to derive insights using Natural Language Processing).
- Context:
- It can (typically) include an NLP Data Scientist Role Overview, which outlines the primary function and objectives of the NLP Data Scientist role.
- It can (typically) include a Text-Data Data Scientist Responsibilities, such as analyzing text data, modeling text datas, and visualizing text data patterns.
- It can (typically) specify Text-Data Data Scientist Skill Requirements, including NLP task proficiency, programming proficiency, knowledge in machine learning frameworks, and familiarity with NLP libraries.
- It can (typically) mention NLP Data Scientist Educational Requirements, often a degree in Data Science, Computer Science, or a related field, with emphasis on NLP and machine learning.
- It can (often) outline NLP Data Scientist Experience Requirements, ranging from entry-level to senior positions, and may include experience with large datasets, cloud computing platforms, and data visualization tools.
- It can (often) include requirements for strong communication and problem-solving skills, essential for collaborating with teams and interpreting complex NLP challenges.
- It can be associated to an NLP Engineer JD.
- ...
- Example(s):
- Junior NLP Data Scientist JD for entry-level NLP data scientists.
- Senior NLP Data Scientist JD for experienced NLP data scientists.
- NLP Analyst JD for roles focusing on text and speech analysis.
- NLP Research Data Scientist JD for NLP research scientists.
- GenAI NLP Data Scientist JD for GenAI NLP data scientists.
- ...
- Counter-Example(s):
- See: Data Scientist JD, Machine Learning Data Scientist JD, AI Data Scientist JD, Job Description.
References
2024
- Bard
- Summary: NLP data scientists are a unique blend of data science and linguistics expertise. They use their knowledge of natural language processing (NLP) to extract meaning from text and speech data, and then use that information to build AI-powered applications like chatbots, sentiment analysis tools, and machine translation systems.
- Responsibilities:
- Data Acquisition and Preprocessing: Identify and collect relevant text and speech data, clean and pre-process the data for analysis, and prepare it for modeling.
- Model Building and Training: Develop and train NLP models for tasks like text classification, sentiment analysis, named entity recognition, and machine translation. This may involve using deep learning techniques such as recurrent neural networks (RNNs) and transformers.
- Evaluation and Optimization: Evaluate the performance of NLP models, identify areas for improvement, and fine-tune the models to achieve optimal results.
- Deployment and Monitoring: Deploy NLP models into production environments, monitor their performance, and make adjustments as needed.
- Research and Development: Stay up-to-date on the latest advancements in NLP research and explore new ways to apply NLP technology to solve real-world problems.
- Skills and Qualifications:
- Master's degree in data science, computer science, linguistics, or a related field (Ph.D. preferred).
- Strong understanding of NLP concepts and techniques.
- Proficiency in programming languages such as Python and R.
- Experience with NLP libraries and frameworks such as spaCy, NLTK, TensorFlow, and PyTorch.
- Excellent analytical and problem-solving skills.
- Strong communication and collaboration skills.
2023
- https://careers.lilly.com/us/en/job/R-55420/GenAI-NLP-Data-Scientist
- Generative AI – Proactive, Predictive, Powerful!
- Are you passionate about using data and technology to answer business and scientific questions? If so, bring YOUR skills and talents to Lilly where you’ll have the chance to create an impact on the lives of patients.
- What You'll Be Doing:
- As a GenAI Data Scientist, you will implement generative AI models, and identifying insights that can be used to drive business decisions. You will work closely with multi-functional teams to understand business problems, develop hypotheses, and test those hypotheses with data.
- How You'll Succeed:
- Develop and implement enterprise-level GenAI models and tools to solve business problems.
- Collaborate with customers to identify business problems and provide data-driven solutions.
- Communicate insights and recommendations to technical and non-technical customers.
- Conduct research to identify emerging trends and technologies in Gen AI and other areas of data science.
- Run and prioritize multiple projects simultaneously.
- Ensure data quality and accuracy.
- What You Should Bring:
- Experience working with cloud based platforms (example: AWS, Azure or related)
- Strong problem-solving and analytical skills
- Proficiency in handling various data formats and sources
- Prior statistical modeling experience
- Demonstrable experience with deep learning algorithms and neural networks
- Experience with data engineering and data pipeline development
- Proven leadership and project management skills.
- Superb communication and presentation skills
- Ability to work in a fast-paced, collaborative environment
- Your Basic Qualifications:
- PhD in computer science, information science, mathematics, statistics, engineering, or related field OR Master's in computer science, information science, mathematics, statistics, engineering, or related field with the following
- 2+ years of experience post education in a NLP/GenAI role
- Experience with machine learning and GenAI algorithms such as large language models
- Prior experience working with Python or other programming languages
- Generative AI – Proactive, Predictive, Powerful!