Data Scientist
2 weeks ago
Ideal Candidate Profile :
Educational Qualifications :
- Bachelor's Degree: B.Tech in Computer Science or B.Stat.
- Master's Degree (Full-Time): A Master's degree in Computer Science, AI/ML, Data Science, or Statistics is required.
Preferred : A PhD in one of these fields is highly desirable.
Industry Experience :
- For candidates with a Master's degree, a minimum of 6 years of relevant industry experience is required.
- For candidates with a PhD, at least 2 years of relevant industry experience is needed.
Skills and Expertise :
1. Data Structures and Algorithms :
- The candidate must have excellent knowledge of Data Structures and Algorithms, with a focus on efficiently solving complex problems through optimized approaches.
2. Programming Skills :
- Python: The candidate should have strong programming skills in Python, with hands-on experience in developing AI/ML algorithms and working on data analysis projects.
- C++: A working knowledge of C++ is essential to complement AI/ML model development, particularly for integrating algorithms into product pipelines.
3. Expertise in AI/ML & Data Science :
- Artificial Intelligence/Machine Learning (AI/ML): Extensive experience in designing, developing, and deploying AI/ML solutions.
4. Data Science : The candidate should have experience in applying data science techniques such as classification and clustering, with a strong understanding of statistical methods.
5. Deep Learning Frameworks : Proficiency in working with Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN) for solving advanced problems.
6. Large Language Models (LLM) : Understanding and experience in working with Large Language Models for natural language processing tasks and other related applications.
Job Responsibilities :
1. AI/ML Algorithm Development :
- The primary responsibility is to design and develop AI/ML algorithms to address complex technical challenges, specifically in the context of 3GPP standards (Third Generation Partnership Project).
- This involves leveraging AI to provide innovative solutions for telecom technologies.
2. Documentation and Presentation :
- The candidate will be responsible for documenting the design and functionality of the developed data science and AI/ML algorithms in clear and precise language.
- Additionally, they will need to present the algorithms and their results to both technical and non-technical stakeholders to support ongoing innovations.
3. Team Collaboration and Integration :
- The candidate will work closely with cross-functional teams to ensure the seamless integration, productization, and deployment of AI/ML models into the product pipeline.
- They will also share responsibilities with the team, ensuring all stages of the AI/ML model lifecycle-from development to deployment-are managed efficiently.
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