> Markdown version of [/jobs/ext/1954987-data-scientist-india](https://www.wearedevelopers.com/jobs/ext/1954987-data-scientist-india). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Data Scientist - INDIA

- **Company:** VYTWO TECHNOLOGIES INC.
- **Location:** Prosper, TX, United States (Remote available)
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Analysis, Microsoft Azure, Big Data, Continuous Integration, Extract Transform Load (ETL), Distributed Computing Environment, Memory Management, Github, Monitoring of Systems, Machine Learning, Tensorflow, Azure Machine Learning, Search Technologies, Unstructured Data, Real Time Systems, Feature Engineering, GitHub Copilot, Pytorch, Large Language Models, Prompt Engineering, Deep Learning, Containerization, Data Lakes, Pyspark, Git Flow, Core Data, Kubernetes, HuggingFace, Production Code, Apache Kafka, Azure AKS, Spark Streaming, Data Management, Machine Learning Operations, Video Streaming, Virtual Agents, Restful APIs, Document Classification, Software Version Control, Data Pipelines, Docker, Databricks
- **Published:** August 6, 2026
- **Apply:** https://www.wayup.com/i-j-Data-Scientist-INDIA-Vytwo-078383807842387/

## 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., Core Skills
Strong hands-on experience with Databricks (Delta Lake, MLflow, Job Orchestration).
Excellent PySpark 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
TensorFlow
Transformers (HuggingFace)
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 (LangChain, Semantic Kernel, CrewAI, AutoGen, 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, EventHub, Spark Streaming).
Understanding of CI/CD for ML (Azure DevOps / GitHub 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.

## Description

Structured Data - Machine Learning & Analytics
Build, deploy, and optimize ML models for predictive analytics, forecasting, classification, and regression.
Perform large-scale feature engineering using PySpark 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 PyTorch, TensorFlow, 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 GitHub Copilot, Claude Code, etc.
Implement model monitoring, observability, drift detection, and performance tracking.


## Related Videos

- [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data)
- [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next)
- [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered)
- [Hacking AI at the Edge of the Indian Ocean](https://www.wearedevelopers.com/videos/100177-hacking-ai-at-the-edge-of-the-indian-ocean)
- [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail)
- [Empowering Retail Through Applied Machine Learning](https://www.wearedevelopers.com/videos/976-empowering-retail-through-applied-machine-learning)

## Related Articles

- [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts)
- [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers)
- [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production)
- [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer)
- [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift)
- [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline)