IN_Senior Associate_Python_Data and Analytics_ Advisory_Bangalore

Line of Service Advisory Industry/Sector Not Applicable Specialism Operations Management Level Senior Associate Job Description & Summary 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 Git 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 Software Development 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?

No Government Clearance Required? No Job Posting End Date July 8, 2026