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Line of Service Advisory Industry/Sector Technology Specialism Advisory - Other Management Level Senior Associate Job Description & Summary As a Machine Learning Engineer you will use techniques such as machine learning and natural language processing to realise authentic, data-driven change and solutions.The team reports to the board and commercial executive and works with clients and PwC leadership across our business units to enhance performance and have impact on value creation. Responsibilities Designing and developing data science and machine learning assets for PwC and its clients Contributing effective, useful code to our Data Science codebase Participating in constant learning through training and skills development Deploying and managing machine learning models in production environments, ensuring scalability, reliability and performance monitoring Embedding Responsible AI practices across the model lifecycle, ensuring fairness, transparency, explainability, bias mitigation and compliance with ethical and regulatory standards Contributing to the strategy and growth of a fast developing data science capability Craft and communicate compelling business “stories” based on analytics insight Business case and Proposal development Presenting findings to senior internal and external stakeholders Being part of this technology innovation effort of the Firm Key Skills Required 4+ Years Experience Statistical Analysis & Machine Learning Theory – Excellent understanding of statistics, machine learning techniques and algorithms. Hands-on experience with regression, classification, clustering and other classical statistical models and algorithms – Must have – Advanced Independently formulate hypotheses, choose and justify appropriate statistical tests and interpret results Select, implement and tune ML algorithms (e.g. random forests, SVMs, gradient boosting) end-to-end, and explain the mathematical foundations and assumptions behind them Hands-on experience designing and validating models for regression, classification and unsupervised learning tasks Deep understanding of bias–variance tradeoff, regularization techniques, and feature selection methods Machine Learning Lifecycle Management – Experience delivering end-to-end solutions from data sourcing and preprocessing through model deployment and results interpretation – Must have – Advanced Architect and execute full pipelines—from data ingestion and feature engineering through model training, validation, deployment, monitoring and retraining, using best practices in reproducibility and CI/CD Troubleshoot production issues (drift, latency, scaling) and optimise models for performance and cost Agile Methodologies – Ability to work effectively in an agile delivery environment, participating in sprint planning, stand-ups and retrospectives – Must have – Intermediate Participate effectively in sprint planning, daily stand-ups and retrospectives Break work into user stories, estimate tasks and collaborate with product owners to groom the backlog Requirements Gathering & Translation – Skill in partnering with product owners to translate business needs into data science requirements and success metrics – Must have – Advanced Lead interactions with stakeholders to outline clear business objectives and translate them into measurable data science success metrics. Draft technical specifications and align on KPIs, risk factors and roadmap milestones Data Science Project Execution – Demonstrable track record of completing data science projects (professional, academic or personal) with a clear business focus – Must have – Advanced Own multiple data science projects from proof-of-concept through delivery, ensuring alignment with business value and timelines Document methodologies, maintain reproducible codebases and present actionable insights to senior leadership Python Programming – Strong programming skills in Python, including libraries like pandas, NumPy, scikit-learn and others for data manipulation and modeling – Must have – Advanced Write clean, modular, well-tested Python code Build custom utilities or packages, optimize critical code paths (vectorization, parallelism) and manage dependencies SQL Querying & Data Manipulation – Practical knowledge of SQL for extracting, transforming and loading data from relational databases – Must have – Intermediate Extract and join complex datasets from relational databases, write performant queries (window functions, CTEs) and perform ETL tasks Version Control & Git – Proficiency with Git for source code management, branching strategies, merging, and collaborative workflows – Must have – Intermediate Use feature branching, pull requests and code reviews in a team setting Data Science Communication – Ability to articulate complex data science concepts and results clearly to both technical and non-technical stakeholders – Must have – Intermediate Craft clear, concise narratives around model design, performance and business impact for both technical and non-technical audiences Design and deliver visuals (e.g. dashboards, slide decks, annotated charts) that guide stakeholders through your methodology, results and recommended actions Team Collaboration & Knowledge Sharing – Enjoy working in cross-functional teams and learning from peers, contributing to collective problem-solving – Must have – Intermediate Mentor junior engineers and foster a culture of continuous learning Contribute to peer code reviews, internal tech talks or knowledge sharing sessions Nice to have Deep Learning Frameworks – Proficiency with frameworks such as TensorFlow, PyTorch, Keras, Theano or CNTK for building and training neural networks – Intermediate Cloud Computing Platforms – Experience working in cloud environments (Azure, GCP or AWS), including managing resources, pipelines and scalable deployments – Intermediate Privacy Enhancing Techniques (PETs) – Some experience with homomorphic encryption, federated learning, differential privacy etc. – Intermediate Relevant experience areas Machine Learning, Generative AI, MLOps & CI/CD, Cloud Native ML Services, Required Skills Optional Skills Accepting Feedback, Accepting Feedback, Active Listening, AI Implementation, Analytical Thinking, C++ Programming Language, Communication, Complex Data Analysis, Creativity, Data Analysis, Data Infrastructure, Data Integration, Data Modeling, Data Pipeline, Data Quality, Deep Learning, Embracing Change, Emotional Regulation, Empathy, GPU Programming, Inclusion, Intellectual Curiosity, Java (Programming Language), Learning Agility, Machine Learning {+ 26 more} Desired Languages (If blank, desired languages not specified) Travel Requirements 0% Available for Work Visa Sponsorship? No Government Clearance Required? No Job Posting End Date Show more

Main Responsibilities Collaborate with cross-functional teams to analyze project requirements, design system architecture, and develop robust applications Write, update, and maintain software packages/code to handle specific jobs based on requirement document Conduct code reviews, identify areas for improvement, and implement best practices to maintain code quality, readability, and maintainability Implement security measures and protocols within .Net applications, including authentication, authorization, and data encryption Utilize your strong knowledge of development tools to design and implement scalable and modular applications Own medium to big size module(s) in project(s) and develop it with the minimal supervision from the project lead Train system users in system operation or maintenance Consult with technical leads to clarify program intent, identify problems, and suggest changes Support junior developers’ work Job Qualifications Education: Bachelor’s degree in computer science or equivalent field Professional Experience Experience: 3-5 years Technical Skills C#, ASP NET, WCF, SQL Server Development, Entity Framework, Windows Services, JavaScript, JQuery, HTML, CSS, Bootstrap, MS Reporting Services, .Net Core, Angular JS, Angular CQRS or NTier &Onion architectures are plus Experience with debugging, performance profiling and optimization Interpersonal Skills Communication and presentations Business Writing Detail-oriented and able to prioritize Analytical skills Troubleshooting and problem-solving Apply Now Show more

Line of Service Advisory Industry/Sector Technology Specialism Advisory - Other Management Level Manager Job Description & Summary A career within Cybersecurity and Privacy services, will provide you with the opportunity to help our clients implement an effective cybersecurity programme that protects against threats, propels transformation, and drives growth. As companies pivot toward a digital business model, exponentially more data is generated and shared among organisations, partners and customers. We play an integral role in helping our clients ensure they are protected by developing transformation strategies focused on security, efficiently integrate and manage new or existing technology systems to deliver continuous operational improvements and increase their cybersecurity investment, and detect, respond, and remediate threats. 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. As a Manager, you'll work as part of a team of problem solvers, helping to solve complex business issues from strategy to execution. PwC Professional skills and responsibilities for this management level include but are not limited to: Develop new skills outside of comfort zone. Act to resolve issues which prevent the team working effectively. Coach others, recognise their strengths, and encourage them to take ownership of their personal development. Analyse complex ideas or proposals and build a range of meaningful recommendations. Use multiple sources of information including broader stakeholder views to develop solutions and recommendations. Address sub-standard work or work that does not meet firm's/client's expectations. Use data and insights to inform conclusions and support decision-making. Develop a point of view on key global trends, and how they impact clients. Manage a variety of viewpoints to build consensus and create positive outcomes for all parties. Simplify complex messages, highlighting and summarising key points. Uphold the firm's code of ethics and business conduct. Required Skills Optional Skills Desired Languages (If blank, desired languages not specified) Travel Requirements Not Specified Available for Work Visa Sponsorship? No Government Clearance Required? No Job Posting End Date Show more