Research Data Scientist-AI/LLM Delivery & Dataset Quality (ID 1407)
Posted
marketscope.zohorecruit.com Research Data Scientist-AI/LLM Delivery & Dataset Quality (ID 1407)
Summary
Research Data Scientist in Noida who designs, builds, and deploys ML/LLM solutions — prompt engineering, fine-tuning, evaluation, RAG apps, and dataset-quality benchmarking — using Python, TensorFlow/PyTorch, cloud platforms, and SQL in a client-facing AI delivery environment.
Design, develop, and deploy machine learning models and data science
solutions
Work on LLM-based use cases such as prompt engineering, evaluation, finetuning, and model optimization
Build and optimize pipelines for structured and unstructured data
Develop and evaluate applications using LLMs (e.g., text generation,
classification, summarization, entity extraction)
Conduct prompt engineering and experimentation to improve model outputs
Support model benchmarking, testing, and performance evaluation
Analyze large datasets to extract actionable insights and patterns
Perform exploratory data analysis (EDA) and feature engineering
Build data visualizations and reports for stakeholders
Participate in client-facing technical discussions and presentations
Translate business requirements into AI/ML solutions and solution architectures
Provide consultative insights based on project learnings and industry trends
Work closely with cross-functional teams (engineering, QA, annotation, delivery
leads)
Support end-to-end project lifecycle: requirement gathering → development →
deployment → monitoring
Ensure quality, scalability, and reliability of AI deliverables
Requirements
2–6+ years of experience in data science, machine learning, or AI solutions
Experience working on AI/LLM or NLP-related projects is highly preferred
Exposure to client-facing or delivery environments is a strong advantage
Strong proficiency in Python (NumPy, Pandas, Scikit-learn)
Experience with ML frameworks (TensorFlow, PyTorch)
Hands-on experience with LLMs / NLP tools (e.g., Hugging Face, OpenAI APIs,
embeddings, RAG frameworks)
Support evaluation and benchmarking methodologies used to determine dataset
quality and model performance.
Work with Subject Matter Experts, Quality teams, and Technical Product
Managers to investigate potential data or Ground Truth issues.
Solid understanding of:
o Machine learning algorithms
o Data preprocessing and feature engineering
o Model evaluation and performance metrics
Experience with:
o SQL and large-scale datasets
o Cloud platforms (AWS, Azure, or GCP)
o Version control (Git)
o Strong hands-on programming capability in Python.
Strong analytical and problem-solving skills
Excellent communication skills (written and verbal)
Ability to explain complex technical concepts to non-technical stakeholders
High attention to detail and quality
Collaborative mindset and adaptability in fast-paced environments