PwC
Website:
pwc.com
Job details:
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 Firm's 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 will design, develop, and deploy predictive models and AI-driven solutions that transform complex data into actionable business insights. As a Senior Associate you will analyze complex problems, mentor others, and maintain standards while building meaningful client connections and navigating increasingly complex situations. This role offers the chance to deepen your technical knowledge and grow your personal brand while collaborating with cross-functional teams to deliver scalable analytics solutions.
Responsibilities
- Design and implement predictive models and AI-driven solutions
- Transform intricate data into actionable business insights
- Analyze complex issues and provide practical solutions
- Mentor junior team members and guide their development
- Collaborate with cross-functional teams to enhance analytics capabilities
- Uphold rigorous standards of quality in deliverables
- Build and maintain sturdy client relationships
- Navigate complex situations to deliver impactful results
What You Must Have
- Bachelor's Degree
- 4 years of experience in data science, machine learning, or applied statistics
- Oral and written proficiency in English required
What Sets You Apart
- Bachelor's or Master's Degree in Data Science preferred
- Relevant certifications in Data Science or Machine Learning preferred
- Excelling in programming with Python and R
- Demonstrating experience in building predictive models
- Utilizing SQL for working with datasets
- Applying statistical techniques for model validation
- Familiarity with cloud platforms for model deployment
- Experience with MLOps tools and practices
- Knowledge of large-scale data processing frameworks
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