Senior Data Scientist designing and leading projects to enhance machine learning classifiers for cancer detection. Collaborating with cross - functional teams in a healthcare company focused on early cancer detection.
About the role
- Data Scientist specializing in structured and unstructured data analysis and ML solutions for predictive analytics and NLP. Join a fast-paced team in Hyderabad, India.
Responsibilities
- 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
- 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
- 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
Requirements
- 3–7 years of experience as a Data Scientist
- 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
- Knowledge of LLM-based agentic frameworks (LangChain, Semantic Kernel, CrewAI, AutoGen, etc.)
- Good to Have: Experience with containerization (Docker, Kubernetes, AKS)
- Good to Have: Experience deploying models to production (REST APIs, real-time endpoints)
Benefits
- Flexible work from home options
- Equal opportunity employer
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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