PwC India
Website:
pwc.in
Company:
https://www.linkedin.com/company/pwc-india
Seniority: Mid-Senior level
Industries: Business Consulting and Services
Job details:
Responsibilities:
Models and machine learning
– Conceptualise business problems, drive frameworks, and translate ambiguous asks into solvable analytical problems.
– Transform data science prototypes into production-grade solutions; design AI/ML applications against defined business
and technical requirements.
– Leverage large language and vision-language models for retrieval, extraction and reasoning over unstructured enterprise
data.
– Find and implement the right algorithms and tools, balancing accuracy, latency, interpretability and cost; train, evaluate
and refine.
– Integrate models into the application flow and deploy at scale, with monitoring for drift, degradation and failure.
Data foundation and infrastructure
– Set up the infrastructure for data analysis and mining required to generate actionable insight reliably.
– Use effective feature engineering and pre-processing across structured and unstructured data; select or define annotated
datasets and their quality controls.
– Extend ML libraries and frameworks so they apply across a range of tasks.
Responsible AI, measurement and governance
– Establish responsible-AI practice — model documentation, bias and privacy review, PII minimisation and audit trails.
– Institutionalise measurement — A/B tests, holdouts and causal inference — so every model carries a defensible business
number.
– Create dashboards and visualisations that present data in a logical, decision-ready way to stakeholders.
Team and stakeholders
– Set up and lead your own team, drive the vertical, and develop next-in-line leaders.
– Collaborate with cross-functional teams of diverse backgrounds; communicate insight coherently, working directly with the senior-most leadership.
Mandatory skill sets:
- Strong command of Python and SQL across large datasets, with robust, testable code and sound software architecture.
- Depth in feature engineering, statistics and ML algorithms (regression, classification, clustering, neural networks,time-series), and in Generative AI, NLP and Computer Vision and their business applications.
- Hands-on with language models for retrieval — embeddings, RAG, vector stores, prompt design and evaluation — plus
- MLOps and engineering discipline to ship: experiment tracking, model registry, versioning, containerisation, CI/CD and cloud AI services (AWS / GCP / Azure).
Preferred skill sets:
- Experience in a high-ticket, considered-purchase category — real estate, automotive, BFSI or luxury retail — where the funnel is long and the sample small; geospatial and location analytics; and productionising generative AI in a regulated or PII-sensitive environment.
Years of experience required:
8+ years
Education qualification:
BS/MS in Computer Science
Click on Apply to know more.
