Bangalore, Ka In_senior associate_python_data and analytics_ advisory_bangalore Jobs – 32 Open Jobs Today

At PwC, our people in data and analytics focus on leveraging data to drive insights and make informed business decisions. They utilise advanced analytics techniques to help clients optimise their operations and achieve their strategic goals.

In data analysis at PwC, you will focus on utilising advanced analytical techniques to extract insights from large datasets and drive data-driven decision-making. You will leverage skills in data manipulation, visualisation, and statistical modelling to support clients in solving complex business problems.

*Why PWC

At PwC, you will be part of a vibrant community of solvers that leads with trust and creates distinctive outcomes for our clients and communities. This purpose-led and values-driven work, powered by technology in an environment that drives innovation, will enable you to make a tangible impact in the real world. We reward your contributions, support your wellbeing, and offer inclusive benefits, flexibility programmes and mentorship that will help you thrive in work and life. Together, we grow, learn, care, collaborate, and create a future of infinite experiences for each other. Learn more about us .

At PwC, we believe in providing equal employment opportunities, without any discrimination on the grounds of gender, ethnic background, age, disability, marital status, sexual orientation, pregnancy, gender identity or expression, religion or other beliefs, perceived differences and status protected by law. We strive to create an environment where each one of our people can bring their true selves and contribute to their personal growth and the firm’s growth. To enable this, we have zero tolerance for any discrimination and harassment based on the above considerations. "

About the Role

We're looking for a Senior AI/ML Engineer who can design, build, and deploy scalable ML, GenAI, and Agentic AI systems across cloud environments (GCP preferred) with strong focus on productionization , automation, and business impact. You'll work across demand forecasting, RAG-based intelligent applications, autonomous multi-agent systems, and enterprise AI integration.

Responsibilities

Build end-to-end ML/AI pipelines (data model deployment monitoring)

Develop and deploy ML, Deep Learning, NLP, and GenAI models in production

Design and implement RAG systems — retrieval, chunking, embeddings, vector search, and prompt engineering

Build Agentic AI solutions — autonomous agents, multi-agent workflows, tool-calling, planning, and memory

Build and optimize time series forecasting models (demand forecasting, inventory planning)

Implement MLOps pipelines — CI/CD, model monitoring, drift detection, governance

Optimize models for performance, cost, and latency

Integrate AI systems with enterprise APIs, data platforms, and customer-facing applications

Design scalable LLM inference architectures for efficient deployment

Collaborate with data scientists, product managers, engineers, and business stakeholders in Agile teams

Debug, optimize , and enhance ML models for quality and performance improvements

Mentor team members and present technical findings to diverse audiences

Stay current with AI/GenAI trends and evaluate emerging tools and frameworks

Mandatory Skills

1. Programming & Core

Python — strong, production-grade coding

SQL — proficient

Data Structures & Algorithms

2. Machine Learning & Deep Learning

Regression, Classification, Clustering, Dimensionality Reduction

Ensemble Models (Random Forest, XGBoost , LightGBM )

CNN, RNN, LSTM, Transformers

Frameworks: Scikit-learn, XGBoost , LightGBM , TensorFlow, Keras , PyTorch

3. Statistics & Mathematics

Probability (Bayesian, Frequentist), Hypothesis Testing, A/B Testing

Regression (Linear, Logistic, GLM), Time Series Analysis

Optimization (convex/non-convex)

Libraries: NumPy, SciPy, Statsmodels

4. ML Pipelines & MLOps

Building end- to- end ML pipelines in production (training, serving, monitoring)

MLOps tools: MLflow , Kubeflow, Vertex AI Pipelines

Model monitoring, drift detection, and governance

5. Cloud — GCP (Primary)

Vertex AI (model training, pipelines, endpoints)

BigQuery , Cloud Storage, Dataproc ( PySpark )

Cloud Composer (Airflow), Cloud Run

6. Generative AI & LLMs

LLMs, advanced prompt engineering

RAG pipelines — retrieval, chunking, embeddings, vector search

VectorDBs : FAISS, Pinecone, Weaviate , ChromaDB , pgvector

Frameworks: LangChain , LlamaIndex , Hugging Face Transformers

7. Agentic AI

Autonomous agents, multi-agent systems

Tool calling, planning, memory, workflow orchestration

Frameworks: LangGraph , CrewAI , AutoGen

Protocols: MCP (Model Context Protocol), A2A (Agent-to-Agent)

8. Time Series / Demand Forecasting

Experience building forecasting models for business prediction

Time series techniques and retail/supply chain forecasting

9. NLP

Text preprocessing, embeddings, NER, classification, sentiment analysis

Semantic search

Frameworks: Hugging Face Transformers, spaCy , NLTK

10. Soft Skills

Strong communication — can present technical concepts to non-technical audiences

Mentoring ability — can guide and uplift junior team members

Analytical thinking with ability to translate business problems into AI solutions

Comfortable working in Agile, cross-functional teams

Good to Have

LLM fine-tuning ( LoRA , PEFT, or full fine-tune on Vertex AI)

LLM serving & inference optimization ( vLLM , GPU memory optimization, model quantization)

Spark / PySpark for large-scale data processing

Computer Vision (image classification, object detection, OCR/Document AI, YOLO, Detectron2)

Recommendation Systems (collaborative filtering, content-based)

Microservices architecture and cloud-based deployments

FastAPI / Flask for API development

MongoDB for data handling and persistence

Multi-cloud exposure (AWS SageMaker, S3, Lambda, ECS/EKS, Step Functions)

Reinforcement Learning

Graph ML / Knowledge Graphs

Distributed computing (Spark, Ray)

ONNX / TensorRT for model optimization

Responsible AI / Explainability

Enterprise Agent Frameworks (Google ADK, AWS Bedrock Agents, Semantic Kernel)

Retail / E-commerce domain experience

What Makes You Stand Out

Built autonomous agents that reason, use tools, and act independently in production

Deployed RAG systems at scale with real users

Experience with multi-agent orchestration (planner-executor patterns)

Built GPU-optimized LLM serving infrastructure

Worked on retail use cases — demand forecasting, recommendations, dynamic pricing, customer segmentation

Built microservices-based AI applications at enterprise scale

Measurable business impact from your AI deployments

Success Criteria

Production-grade AI systems running reliably at scale

Scalable, automated ML/GenAI pipelines

Effective GenAI & Agentic AI deployments solving real business problems

Measurable business impact and stakeholder satisfaction

Mandatory Skill Sets:

Python (strong coding ability) SQL (proficient) Machine Learning & Deep Learning ML Frameworks (Scikit-learn + TensorFlow/PyTorch) Building end-to-end ML Pipelines MLOps (MLflow / Kubeflow / Vertex AI) GCP Cloud (BigQuery, Cloud Composer, Airflow) GenAI / LLM hands-on — RAG pipelinesm Fine-Tuning, prompt engineering (LangChain, LlamaIndex), VectorDB Agentic AI (LangGraph, CrewAI)

Preferred Skill Sets:

Spark / PySpark Working exp with Fast API/Flask NLP / Computer Vision / Recommendation Systems

Years of Experience required:

4-8 yrs

Education Qualification:

B.E, B.Tech, MCA, M.E, M.Tech

Education (if blank, degree and/or field of study not specified)

Degrees/Field of Study required: Bachelor of Engineering

Degrees/Field of Study preferred:

Certifications (if blank, certifications not specified)

Required Skills

Python IDLE

Optional Skills

Accepting Feedback, Accepting Feedback, Active Listening, Algorithm Development, Alteryx (Automation Platform), Analytical Thinking, Analytic Research, Big Data, Business Data Analytics, Communication, Complex Data Analysis, Conducting Research, Creativity, Customer Analysis, Customer Needs Analysis, Dashboard Creation, Data Analysis, Data Analysis Software, Data Collection, Data-Driven Insights, Data Integration, Data Integrity, Data Mining, Data Modeling, Data Pipeline {+ 38 more}

Desired Languages (If blank, desired languages not specified)

Travel Requirements

Not Specified

Available for Work Visa Sponsorship?

Government Clearance Required?

Job Posting End Date

July 8, 2026

Apply Now

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