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Job Description: Data Science Analyst – ITOrizon (AI & Data Platforms)
Location: Bangalore (Full-time, Work from Office)
Experience: 5+ years (Hands-on)
Employment Type: Permanent
Key Responsibilities
- Design, develop, and deploy machine learning, statistical, deep learning, and
Generative AI models for enterprise use cases.
- Perform data exploration, feature engineering, model training, evaluation, and
optimization on structured and unstructured datasets.
- Build predictive, prescriptive, and descriptive analytics solutions aligned with
business objectives.
- Develop and fine-tune AI/ML models including classical ML, Deep Learning, NLP,
Time-Series Forecasting, and Large Language Models (LLMs).
- Design and implement Retrieval-Augmented Generation (RAG) pipelines using
enterprise knowledge sources and Vector Databases.
- Build reusable Prompt Templates and Prompt Engineering strategies for
enterprise AI applications.
- Apply Anthropic Constitutional AI principles to develop safe, reliable, and
responsible AI applications.
- Collaborate with Data Engineering and Platform teams to productionize models
using MLOps and LLMOps best practices.
- Develop AI experimentation, evaluation, and benchmarking frameworks using
MLflow and enterprise AI evaluation methodologies.
- Implement model monitoring, explainability, governance, drift detection, and
Responsible AI practices.
- Work with large-scale and real-time datasets, cloud-native AI services, and
enterprise analytics platforms.
- Participate in AI architecture discussions, experimentation frameworks,
innovation initiatives, and enterprise AI strategy.
- Stay current with emerging trends in AI, ML, GenAI, Agentic AI, and enterprise AI
technologies.
Required Skills & Expertise
Core Data Science & AI
- Strong hands-on expertise in Python, which is the primary language used for
AI/ML development.
- Proven experience building production-grade AI/ML solutions using Python
(NumPy, Pandas, Scikit-learn, SciPy).
- Solid foundation in Statistics, Probability, Linear Algebra, and Optimization.
- Experience with machine learning techniques including Regression,
Classification, Clustering, Time Series Forecasting, Recommendation Systems,
and Anomaly Detection.
- Hands-on experience with Deep Learning frameworks such as TensorFlow or
PyTorch.
- Experience working with Large Language Models (LLMs), embeddings, semantic
search, and Retrieval-Augmented Generation (RAG).
- Willingness and ability to learn and work with other programming languages
(e.g., Java, Scala, SQL, or platform-specific languages) as required by enterprise
platforms and integrations.
Generative AI & LLM Engineering
- Hands-on experience with Prompt Engineering, Prompt Templates, Few-shot
Prompting, Chain-of-Thought Prompting, and Structured Output Generation.
- Experience with Anthropic Claude, OpenAI GPT, Google Gemini, Azure OpenAI,
or Amazon Bedrock.
- Knowledge of Anthropic Constitutional AI principles, system prompt design,
guardrails, and AI safety.
- Experience with Function Calling, Tool Use, AI Agents, and workflow
orchestration.
- Familiarity with Vector Databases such as Pinecone, Milvus, Weaviate,
ChromaDB, or FAISS.
- Exposure to AI frameworks such as LangChain, LangGraph, LlamaIndex,
Semantic Kernel, DSPy, CrewAI, or AutoGen.
- Understanding of LLM evaluation, prompt optimization, hallucination mitigation,
and Responsible AI.
Data & Platforms
- Experience working with SQL and NoSQL databases.
- Understanding of data pipelines, ETL/ELT processes, Feature Engineering
workflows, and Feature Stores.
- Hands-on exposure to cloud platforms (AWS and/or Azure) for Data Science and
Pay: Up to ₹2,000,000.00 per year
Work Location: In person
