At PwC, our people in data and analytics focus on leveraging data to drive insights and make informed business decisions. They utilise advanced analytics techniques to help clients optimise their operations and achieve their strategic goals.
In data analysis at PwC, you will focus on utilising advanced analytical techniques to extract insights from large datasets and drive data-driven decision-making. You will leverage skills in data manipulation, visualisation, and statistical modelling to support clients in solving complex business problems.
Focused on relationships, you are building meaningful client connections, and learning how to manage and inspire others. Navigating increasingly complex situations, you are growing your personal brand, deepening technical expertise and awareness of your strengths. You are expected to anticipate the needs of your teams and clients, and to deliver quality. Embracing increased ambiguity, you are comfortable when the path forward isn’t clear, you ask questions, and you use these moments as opportunities to grow.
Skills
Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to:
Respond effectively to the diverse perspectives, needs, and feelings of others.
Use a broad range of tools, methodologies and techniques to generate new ideas and solve problems.
Use critical thinking to break down complex concepts.
Understand the broader objectives of your project or role and how your work fits into the overall strategy.
Develop a deeper understanding of the business context and how it is changing.
Use reflection to develop self awareness, enhance strengths and address development areas.
Interpret data to inform insights and recommendations.
Uphold and reinforce professional and technical standards (e.g. refer to specific PwC tax and audit guidance), the Firms code of conduct, and independence requirements.
The Opportunity
When you join PwC Acceleration Centers (ACs), you step into a pivotal role focused on actively supporting various Acceleration Center services, from Advisory to Assurance, Tax and Business Services. In our innovative hubs, you’ll engage in challenging projects and provide distinctive services to support client engagements through enhanced quality and innovation. You’ll also participate in dynamic and digitally enabled training that is designed to grow your technical and professional skills.
As part of the Data and Analytics team you lead the analysis of complex supply chain problems and drive the development of data science solutions. As a Senior Associate, you guide and mentor junior team members while maintaining the integrity and quality of deliverables. This role offers the chance to collaborate with clients and consultants, leveraging advanced analytics tools to provide impactful business recommendations.
Responsibilities
Conduct data analysis to support supply chain initiatives
Collaborate with teams to identify data-driven solutions
Develop and implement analytical models for insights
Present analytical findings to enhance operational effectiveness
Mentor team members on data analysis techniques
Maintain data quality and compliance with standards
Stay informed on emerging data technologies
Contribute to strategic planning through data insights
Well versed and hands-on experience of working on optimization methods like linear programming, mixed integer programming, scheduling optimization. Having understanding of working on third party optimization solvers like Gurobi will be an added advantage
Proficiency in forecasting techniques (e.g., Holt
Winters, ARIMA, ARIMAX, SARIMA, SARIMAX, FBProphet, NBeats) and machine learning techniques (supervised and unsupervised)
Experience using at least one major cloud platform (AWS, Azure, GCP), such as:
Aws
Experience with AWS SageMaker, Redshift, Glue, Lambda, QuickSight
Azure
Experience with Azure ML Studio, Synapse Analytics, Data Factory, Power BI
Gcp
Experience with BigQuery, Vertex AI, Dataflow, Cloud Composer, Looker
Experience developing, deploying, and monitoring ML models on cloud infrastructure
Expertise in Python, SQL, data orchestration, and cloud-native data tools
Hands-on experience with cloud-native data lakes and lakehouses (e.g., Delta Lake, BigLake)
Familiarity with infrastructure-as-code (Terraform/CDK) for cloud provisioning
Knowledge of visualization tools (PowerBI, Tableau, Looker) integrated with cloud backends
What Sets You Apart
Advanced Degree in a quantitative discipline
Proven leadership in supply chain analytics projects
Demonstrating proficiency in forecasting and machine learning techniques
Utilizing GCP tools for data analysis and modeling
Building data pipelines for optimization and scenario planning
Excelling in SQL and Python programming skills
Familiarity with MLOps and containerization tools
Engaging effectively with stakeholders at the executive level
Experience in driving design and delivery of data science solutions
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