At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven decision making. You will work on developing predictive models, conducting statistical analysis, and creating data visualisations to solve 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 OpportunityWhen 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 Science and Machine Learning Engineering team you the development and implementation of sophisticated machine learning models and algorithms for GenAI projects. As a Senior Associate you analyze complex problems, mentor others, and maintain standards while building meaningful client connections and your technical. Join us to drive significant advancements in GenAI solutions and enjoy a collaborative work environment that fosters professional growth.
Responsibilities
- Lead the design and execution of advanced machine learning models for GenAI initiatives
- Analyze intricate challenges and provide creative solutions
- Mentor junior team members to enhance their technical skills
- Foster sturdy relationships with clients to understand their needs
- Maintain elevated standards of quality in deliverables
- Collaborate with cross-functional teams to drive project success
- Stay updated on industry trends and emerging technologies
- Contribute to the continuous improvement of processes and methodologies
What You Must Have
- Bachelor's Degree
- 4 years of experience in data science or machine-learning-driven product development
- Oral and written proficiency in English required
What Sets You Apart
- Bachelor's or Master's in Computer Science, Data Science, Statistics
- Certifications in cloud technologies, Kubernetes, or GenAI
- Leading GenAI or LLM initiatives
- Managing project teams effectively
- Advanced programming in Python
- Utilizing machine learning libraries like TensorFlow, PyTorch
- Implementing Model Context Protocol (MCP)
- Enhancing model performance through fine-tuning
- Experience with agent orchestration platforms
