Pwc
IN_Associate_DataScientist,GenAI_Data&Analytics_Advisory_PANIndia
Neural analysis suggests this role is
optimal for Associate candidates.
“IN_Associate_Data Scientist, Gen AI_Data & Analytics_Advisory_PAN India at Pwc. Skills: Generative AI, Data Science, Python, R, SQL, DL, ML algorithms, Text Analytics, LLM Ops, ML Ops, PyTorch, TensorFlow. Designing and building analytical /DL/ ML algorithms using Python, R and other statistical tools.. data representation and lucid presentation (of analysis/modelling output) using Python, R Markdown”
What You'll Achieve.
transforming raw data into actionable insights; enabling informed decision-making; driving business growth
Industry & Context.
transforming raw data into actionable insights; enabling informed decision-making
What They're Looking For.
Must Have
BE, B. Tech, M. Tech, 3-10 Years of experience, SQL, R/Python
Nice to Have
Generative AI (Design, development of GenAI application in production), RAG, Vector Database, Lang Chain and multimodal AI applications, deploying and optimizing AI application in production, statistical and data mining techniques like Linear & Logistic Regression analysis, Decision trees, Bagging, Boosting, Time Series and Non-parametric analysis, DL & Neural Network Architectures (CNN, RNN, LSTM, Transformers etc. ), advanced Text Analytics (NLP, NLU, NLG), LLM Ops, ML Ops for scalable ML development, Generative AI services like OpenAI, Google (Gemini), Agentic AI Framework (Lang Graph, Auto gen etc. ), fine-tuning for pre-trained models like GPT, LLaMA, Claude etc. using LoRA, QLoRA and PEFT technique
What You'll Do.
Designing and building analytical /DL/ ML algorithms using Python
R and other statistical tools.
data representation and lucid presentation (of analysis/modelling output) using Python
Ability to learn new scripting language or analytics platform.
Designing and building data infrastructure and systems to enable efficient data processing and analysis.
developing and implementing data pipelines
and data transformation solutions.
How You'll Work.
Communication Scope
lucid presentation (of analysis/modelling output)
Full Job Description
**Line of Service** Advisory **Industry/Sector** Not Applicable **Specialism** Data, Analytics & AI **Management Level** Associate **Job Description & Summary** At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. In data engineering at PwC, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis. You will be responsible for developing and implementing data pipelines, data integration, and data transformation solutions. _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](https://www.pwc.in/about-us.html). 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. **Job Description & Summary: *
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