Data Scientist-Manager

PwC
5 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English

Job location

Tech stack

Mxnet
Agile Methodologies
Artificial Intelligence
Amazon Web Services (AWS)
Azure
Python
TensorFlow
SQL Databases
Feature Engineering
PyTorch
Deep Learning
Keras
GIT
Core Data
Machine Learning Operations
Software Version Control
Devsecops
Programming Languages

Job description

  • Working as part of a cross-functional product squad - including AI Engineers, Product Designers, Data Scientists and Industry Sector Specialists - to launch and scale AI client solutions, from core data science products (e.g. pricing and forecasting) all the way through to Agentic AI
  • Designing and advising on the data science approach for your product, balancing rigour, interpretability, and scalability, and ensuring models are reusable across multiple client contexts
  • Partnering with sector and go-to-market teams and solution architects to identify client challenges, demonstrate product capabilities, gather feedback, and inform development priorities
  • Collaborating closely with engineers to productionise models on cloud platforms (Azure, AWS, or GCP) using MLOps and DevSecOps practices
  • Working with the Product owner to monitoring model performance and user feedback to continuously refine algorithms, enhance feature design, and improve product outcomes over time
  • Embedding responsible and explainable AI principles into development to ensure outputs are trusted, transparent, and compliant with PwC's standards

Requirements

Demonstrable practical project experience (professional or academic) in using applied analytics to solve business problems, including:

  • Practical experience across the data science lifecycle - from feature engineering and model design to validation, deployment, and monitoring;
  • Fluency in Python, SQL, or similar programming languages;
  • Experience using deep learning frameworks such as TensorFlow, Keras, PyTorch, or MXNet;
  • Familiarity with Agile and DevSecOps practices, including use of Git for version control;
  • Exposure to cloud environments (Azure, AWS or GCP) and a desire to build solutions that scale;
  • The ability to explain complex data concepts clearly to technical and non-technical audiences, with strong data storytelling and visualisation skills;
  • Intellectual curiosity with a disciplined, hypothesis-led approach - validating, challenging, and refining your outputs to ensure analytical rigour and business relevance
  • Commercial curiosity and the desire to understand how analytics drives business outcomes;
  • A collaborative mindset - you enjoy working in diverse, cross-functional teams that have a blend of onshore and offshore resources

About the company

PwC provides services to 420 out of 500 Fortune 500 companies. The firm was formed in 1998 by a merger between Coopers & Lybrand and Price Waterhouse.

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