Principal Data Scientist
2 days ago
Job Description :
Role : Principal Data Scientist / LLM Specialist
Responsibilities :
1. Strategic Leadership :
a. Define and drive the overall data science strategy and roadmap for the organization, aligning it with business objectives and technical capabilities.
b. Oversee the design, development, and implementation of data science solutions.
c. Foster a culture of innovation and continuous improvement within the data science team.
2. Data Strategy :
a. Develop and deploy advanced data science models and algorithms, including LLMs, to solve complex business problems. Identify, acquire, and curate high-quality datasets relevant ML tasks.
b. Design and implement data preprocessing, cleaning, and augmentation techniques.
c. Leverage LLMs to extract deeper insights from data, including unstructured text and natural language data.
3. Data-Driven ML Development :
a. Collaborate with LLM experts to integrate LLMs into data science pipelines and applications.
b. Optimize LLM performance for specific tasks and domains.
c. Apply advanced data mining and machine learning techniques to extract valuable insights.
d. Evaluate ML performance using rigorous data-driven metrics.
4. ML Data Visualization and Analysis :
a. Develop data visualizations and analysis techniques to understand ML Al behavior and performance.
b. Identify trends, patterns, and anomalies in data. Explore new applications of LLMs in data science, such as LLM-powered recommendation systems, predictive analytics, and anomaly detection.
c. Communicate data-driven insights to stakeholders effectively.
Minimum Required Skills :
- 11+ years of experience preferred.
- Advanced degree in computer science, data science, or a related field.
- Deep understanding of LLM architectures, algorithms, and techniques.
- Strong experience in Python, SQL.
- Should be extremely comfortable with Numpy, Pandas, Matplotlib and Scikit learn python libraries
- Strong understanding of machine learning concepts and algorithms. Should know deep learning techniques such as clustering, decision trees, random forest, etc.
- Knowledge on text classification, sentiment analysis, named entity recognition, machine translation, text summarization and question-answering is must.
- Experience with LLM frameworks (Hugging Face Transformers, TensorFlow, PyTorch)
- Experience with data labeling and annotation tools.
- Certifications in cloud platforms or ML technologies can be a plus.
- Proficient knowledge of cloud platforms (AWS, GCP, Azure).
- Strong problem-solving and analytical skills.
- Ability to work in team-oriented, collaborative environment.
Keywords :
- Data Scientist
- Statistician
- Data Engineer
- Python
- R
- Supervised & Unsupervised learning
- Machine Learning Algorithms
- Deep Learning
- Hugging Face
- Natural Language Processing (NLP)
- Computer Vision
- TensorFlow
- PyTorch
- Scikit-learn
- Transformers
- LLM Frameworks
- LLM Models
- GPT -3, 4o
- BERT
- Llama
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