Senior Data Scientist
Providence is hiring a Senior Data Scientist in Hyderabad (hybrid) to build end-to-end data science solutions spanning rigorous statistics, classical ML, and Generative AI — designing RAG pipelines, fine-tuning LLMs, and deploying predictive models to production. Core stack: Python, SQL, PyTorch, LangChain/LlamaIndex, and vector databases.
- Compensation
- Not disclosed
- Location
- Hyderabad, IN
- Work setup
- Not specified
- Seniority
- Senior
- Employment
- Full time
- Experience
- Not specified
- Category
- Data science
- Posted
Skills
Must have
- Bachelor's, Master's, or Ph.D. in Computer Science, Statistics, Applied Mathematics, Data Science, Quantitative Finance, or a related quantitative field
- Strong expertise in probability distributions, stochastic processes, decision theory, regression analysis, and variance reduction techniques
- Proficiency with ML frameworks (scikit-learn, XGBoost, LightGBM, PyTorch, or TensorFlow)
- Deep understanding of loss functions, optimization algorithms, evaluation metrics (ROC-AUC, RMSE, Precision/Recall, BLEU, ROUGE), and cross-validation techniques
- Practical experience with LLM frameworks like LangChain, LangGraph, LlamaIndex, or DSPy
- Hands-on experience with Vector Databases (ChromaDB, Pinecone, pgvector, Qdrant, or FAISS)
- Knowledge of quantization techniques (LoRA, QLoRA), embedding models, and multi-agent coordination frameworks (e.g., MCP servers)
- High proficiency in Python (Pandas, NumPy, SciPy, PyTorch) and complex SQL
- Familiarity with containerization (Docker) and modern development workflows (Git, CI/CD)
Nice to have
- Experience with time-series forecasting, quantitative modeling, or risk prediction algorithms
- Knowledge of MLOps practices, model monitoring, and pipeline orchestration tools
- Familiarity with cloud platforms (AWS, GCP, or Azure)
Full description
Job Description: Senior Data Scientist (Statistics, ML & Generative AI)
Location: Hyderabad, Telangana, India / Hybrid
Role Type: Full-Time
Position Overview
We are looking for a highly analytical and technical Senior Data Scientist with a strong mathematical foundation in statistics, probability, and classical machine learning, paired with cutting-edge experience in Large Language Models (LLMs) and Generative AI.
In this role, you will bridge the gap between rigorous statistical modeling and state-of-the-art AI technologies. You will design, develop, and deploy end-to-end data science solutions, RAG (Retrieval-Augmented Generation) architectures, and predictive models that turn complex data into strategic business value.
Key Responsibilities
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Core Statistical & ML Modeling:
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Apply advanced probability theory, hypothesis testing, Bayesian methods, and statistical inference to validate data distributions, perform predictive analytics, and design robust experiments (A/B testing).
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Build, fine-tune, and evaluate classical machine learning algorithms (regression, classification, clustering, time-series forecasting, ensemble methods) for production systems.
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Generative AI & LLM Engineering:
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Design and implement Generative AI architectures, including Retrieval-Augmented Generation (RAG) pipelines, multi-agent frameworks, and vector search systems.
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Fine-tune, evaluate, and prompt-engineer open-source and proprietary Large Language Models (LLMs) for specific domain applications.
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Implement guardrails, evaluation frameworks (e.g., RAGAS, DeepEval), and toxicity/bias detection for LLM applications.
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Data Engineering & System Architecture:
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Collaborate with engineering teams to deploy ML/LLM models into production microservices via REST APIs, gRPC, or async worker queues.
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Optimize model inference latency, throughput, and GPU/memory consumption.
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Design data pipelines using Python, SQL, and modern data orchestration toolkits.
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Thought Leadership & Collaboration:
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Partner with product and business stakeholders to translate complex business problems into scalable machine learning and AI frameworks.
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