Job Description
Position: Data Scientist: NLP, GenAI & Big Data (Azure)
Role:
Data Scientist - INDIA
Location:
Hyderabad / Noida, India
Consultants local to India are eligible.
Category:
Data Science – Structured Data / Text Data (NLP & GenAI)
About the Role
- We are seeking a highly skilled Data Scientist (3–7 years of experience) to join our team and work across two major data science domains:
- Structured Data (80–90%) – Predictive analytics, forecasting, cost estimation, likelihood modeling, and batch‑oriented machine learning pipelines.
- Text / Unstructured Data (NLP & GenAI) – Building low‑latency real‑time systems using deep learning, LLMs, prompt engineering, and agentic AI frameworks.
- This role requires strong expertise in Big Data processing, modern ML tools, and the ability to build scalable, production‑ready data science solutions.Key Responsibilities Structured Data – Machine Learning & Analytics
- Build, deploy, and optimize ML models for predictive analytics, forecasting, classification, and regression.
- Perform large-scale feature engineering using Py Spark and Big Data tools.
- Work on batch pipelines, model versioning, and experiment tracking.
- Develop cost estimation and risk/likelihood models using statistical and ML techniques. Text Data / NLP / GenAI
- Build NLP pipelines using deep learning frameworks such as Py Torch , Tensor Flow, or similar.
- Develop real‑time, low‑latency inference systems for text classification, embeddings, semantic search, summarization, and retrieval.
- Create prompts, context graphs, and agentic workflows for LLM‑based systems.
- Apply knowledge of prompt engineering, context engineering, and autonomous agent frameworks to production systems. Core Data Science Engineering & MLOps
- Work in Databricks for ETL, feature engineering, ML training, and orchestration.
- Use Azure services for model deployment, data pipelines, and infrastructure.
- Collaborate using Git‑based workflows; leverage tools like Git Hub Copilot , Claude Code, etc.
- Implement model monitoring, observability, drift detection, and performance tracking. Required Skills & Experience Core Skills
- Strong hands‑on experience with Databricks (Delta Lake, MLflow, Job Orchestration).
- Excellent Py Spark skills for large‑scale distributed data processing.
- Proficiency in Azure cloud services (ADF, Azure ML, AKS, Databricks on Azure).
- Strong understanding of ML algorithms, statistical methods, and data analysis.
- Experience with deep learning frameworks: PyTorch, Tensor Flow, Transformers (Hugging Face).
- Experience with model monitoring and ML observability.
- Ability to write clean, optimized code and leverage AI code assistants. NLP / GenAI Specific Skills
- Prompt engineering (task prompts, chain of thought, tool calling, retrieval prompts).
- Context engineering (retrieval pipelines, RAG, memory management, context structuring).
- Knowledge of LLM‑based agentic frameworks (Lang Chain, Semantic Kernel, CrewAI, Auto Gen, etc.).
- Experience with vector databases and embedding models is a plus. Good to Have Skills
- Experience with containerization (Docker, Kubernetes, AKS).
- Experience deploying models to production (REST APIs, real‑time endpoints).
- Knowledge of streaming technologies (Kafka, Event Hub, Spark Streaming).
- Understanding of CI/CD for ML (Azure Dev Ops / Git Hub Actions). Who You Are
- A problem solver who is comfortable working with both structured and unstructured data.
- Someone who enjoys using modern AI tools to accelerate development.
- A data scientist who writes clean, production‑grade code.
- A collaborator who thrives in cross‑functional teams and fast‑paced environments.
Flexible work from home options available.
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