Director - Data Science-Conversational AI

Key Skills

Aartificial intelligence, Apache Airflow, AWS, Azure, Big Data Technology, Caffe, CNNs, Data science techniques, Effective communication skills, Google Cloud Platform (GCP), H2O, Large Language Models - LLMs, Machine learning techniques, Natural Language Processing (NLP), Natural Language Understanding-NLU, PowerBI, Presentation skills, PySpark, Python Programming, RNNs, SQL, Tableau, TensorFlow

Job Description

• career in our Analytics Insight practice, within Cloud and Digital services, will provide you with the opportunity to focus on the cutting edge of developments in the Cloud, Big Data and the world of AI/ML, which bring new and innovative services to some of the leading firms globally.

  We help our clients adopt technologies and environments which can transform the business and operational environments within the enterprise.

  Our team helps organizations transform their Data and Analytics infrastructure, modernize applications and data management to help shape the future of business. As part of the team, you’ll focus on various data and analytics platforms, cloud environments, architecture, application development, application modernization, data warehouse, data management and industry solutions to deliver innovation for our clients.

  To really stand out and make us fit for the future in a constantly changing world, each and every one of us at PwC needs to be a purpose-led and values-driven leader at every level. To help us achieve this we have the PwC Professional; our global leadership development framework. It gives us a single set of expectations across our lines, geographies and career paths, and provides transparency on the skills we need as individuals to be successful and progress in our careers, now and in the future.

  Must Have below skills:

  • Solid knowledge and experience of supervised, unsupervised and reinforcement learning machine
  • learning algorithms. For e.g: classifiers, cluster analysis, dimension reduction, regression, and
  • models CNN, RNN, DQN, GAN, temporal difference methods, sequence modeling, NLP/NLU,
  • word/doc embeddings, collaborative filtering, self-attention, transformers, etc.
  • Experience with the current state of AI/ML, Large Language Models, and Generative AI
  • Fine-tune language models to specific domains using LLM to improve the accuracy and
  • effectiveness of text-based applications
  • Build generative AI models that can generate original content, such as text, images, or music
  • Experience with model explainability and interpretability techniques
  • Experience in machine learning frameworks and tools ( For e.g: scikit-learn, mlr, caret, H2O, TensorFlow,
  • MXNet, Pytorch, Caffe/Caffe2, CNTK, MLlib)
  • Advanced level programming in SQL and Python/Pyspark to guide teams
  • Lead and manage a team of data scientists and engineers working on generative AI projects
  • Identify and evaluate new AI technologies and tools that could be leveraged for generative AI projects.
  • Understand the nuances between traditional Machine Learning lifecycle and Generative AI modeling
  • lifecycle
  • Develop and implement ethical guidelines and standards for AI development and deployment
  • Stay up to date with the latest research and trends in the field of generative AI and apply them to the

  company's projects and goals

  • Communicate effectively with stakeholders at all levels of the organization to explain the benefits and risks

  of generative AI solutions