IN_Senior Manager_Data Science & AI_OC-Data & Analytics_Advisory_Bhubaneswar

Line of Service Advisory Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Manager 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 . 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: We are seeking a highly skilled and visionary Senior Manager – Data Science & AI to lead our advanced analytics and AI/ML initiatives, including next-generation technologies like Generative AI and Agentic AI.

The ideal candidate will be responsible for managing data science teams, driving innovation in machine learning model development, and operationalizing AI solutions that deliver measurable business value.

Responsibilities

• Lead, mentor, and scale a team of data scientists, ML engineers, and AI researchers working on predictive analytics, generative AI models, and agentic AI systems.
• Define the AI/ML strategy aligned with business goals and emerging technology trends, including GenAI and agentic AI capabilities.
• Oversee the full ML lifecycle: problem formulation, data acquisition, feature engineering, model development, validation, deployment, and monitoring.
• Drive the research and development of advanced AI models, including generative models (e.g., GPT, diffusion models), reinforcement learning agents, and autonomous AI systems.
• Collaborate with product, engineering, and data engineering teams to integrate AI/ML solutions into scalable production environments.
• Implement best practices for MLOps, model governance, explainability, and ethical AI.
• Evaluate and adopt state-of-the-art AI technologies, frameworks, and tools (e.g., Tensor. Flow, Py. Torch, Hugging Face, Lang. Chain).
• Champion the use of generative AI for use cases such as content generation, code synthesis, conversational agents, and decision automation.
• Manage cross-functional projects and collaborate with stakeholders to prioritize AI initiatives based on business impact.
• Stay abreast of industry research and contribute to AI community engagement, publications, or conferences as appropriate. Mandatory skill sets:
• Strong background in Data Science, Machine Learning, Artificial Intelligence, with hands-on experience in developing and deploying models in production.
• Deep knowledge of Generative AI technologies — experience working with models such as GPT, BERT, DALL-E, diffusion models, or other generative architectures.
• Understanding of Agentic AI concepts including reinforcement learning, autonomous decision-making systems, and intelligent agents.
• Proficiency in ML frameworks and libraries: Tensor. Flow, Py. Torch, Scikit-learn, Hugging Face Transformers, Lang. Chain, etc.
• Programming expertise in Python and experience with related ML/AI libraries.
• Experience with MLOps practices and tools for CI/CD of machine learning models (e.g., Kubeflow, MLflow, TFX).
• Solid grasp of data engineering basics and ability to collaborate effectively with data engineering teams.
• Familiarity with cloud platforms (Azure ML, AWS Sage. Maker, Google Vertex AI, Oracle AI services) for model training and deployment.
• Knowledge of AI ethics, fairness, bias mitigation, privacy, and explainability. Leadership & Management:
• Proven experience managing data science, ML, or AI teams.
• Ability to translate complex AI technologies into business value and actionable insights.
• Strong communication and stakeholder management skills.
• Experience working in agile delivery environments and managing cross-functional resources.
• Demonstrated ability to mentor and develop technical talent. Preferred skill sets:
• Master’s or PhD degree in Computer Science, Artificial Intelligence, Machine Learning, Statistics, or related field.
• Publications or patents in AI fields or participation in AI research communities.
• Experience in deploying AI-powered conversational agents, digital assistants, or autonomous AI systems.
• Familiarity with natural language processing (NLP), computer vision, or speech AI applications.
• Experience with agentic or autonomous AI frameworks and tooling. Years of experience required: 12 to 16 years Education qualification: Graduate Engineer or Management Graduate Education (if blank, degree and/or field of study not specified) Degrees/Field of Study required: MBA (Master of Business Administration), Bachelor of Engineering Degrees/Field of Study preferred: Certifications (if blank, certifications not specified) Required Skills Data Engineering Optional Skills Accepting Feedback, Accepting Feedback, Active Listening, Agile Scalability, Amazon Web Services (AWS), Analytical Thinking, Apache Airflow, Apache Hadoop, Azure Data Factory, Coaching and Feedback, Communication, Creativity, Data Anonymization, Data Architecture Development, Database Administration, Database Management System (DBMS), Database Optimization, Database Security Best Practices, Databricks Unified Data Analytics Platform, Data Engineering, Data Engineering Platforms, Data Infrastructure, Data Integration, Data Lake, Data Modeling {+ 37 more} Desired Languages (If blank, desired languages not specified) Travel Requirements Available for Work Visa Sponsorship? Government Clearance Required? Job Posting End Date July 7, 2026