Data Scientist
Job Description
- Experience with Programming (Python, SQL, NoSQL, Spark) and ML tools and cloud technologies (AWS, Azure, GCP).
- Deep understanding of ML algorithms for common use cases in both structured and unstructured data systems. - Experience with GenAI/ LLM tools (3-6 years practitioner in data science): LangChain, RAG pipelines, Embeddings & vector databases, Multi-modal LLMs, Fine-tuning techniques ()
- Experience in building FastAPI-based services and Dockerized deployments
- Experience building production-grade GenAI solutions
- Familiarity with: - Multi-agent architectures and orchestration
- Exposure to enterprise analytics / BI tools: - Power BI, Tableau, or other visualization tools
- Experience collaborating with UI/UX teams for AI-driven solution delivery
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Key Skills
About Company
Skills:
Pyspark, Machine Learning, Hive, Python, Statistical Analysis, Sql, Generative AI, AI-powered applications, LLMs
Skills:
Pyspark, Python, Programming, R, Visualization, Data Interpretation, Model development and validation, Building and evaluating algorithms, SQL querying, Evaluating regression problems
Skills:
Python, Sql, AI fluency, Data Quality Checks, LLMs, Data Pipelines, data infrastructure, data models
Skills:
Predictive Modeling, Machine Learning, Python, Sql, Statistical Analysis
Skills:
Machine Learning, Neural Networks, Dynamo Db, Apis, Python Programming, AWS Bedrock, Embedding generation, Similarity search, Llm, Agentic AI, Claude LLMs, Document ingestion, prompt tuning, multi-step reasoning, AgentCore, Human-in-the-loop mechanisms, Simple Autonomous agents, vector databases, Guardrails, logging and observability, prompt engineering, tool-calling agent orchestration, workflow automation, output evaluation