Engineering
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Specialty/Competency: Data Science Industry/Sector: Not Applicable Time Type: Full time Travel Requirements: Up to 20% 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. Driven by curiosity, you are a reliable, contributing member of a team. In our fast-paced environment, you will have the chance to work on a variety of assignments, each presenting varying challenges and scope. Every experience is an opportunity to learn and grow. You are encouraged to ask questions, take initiative, and produce quality work that adds value for our clients and contributes to our team’s success. During your time at the Firm, you start to establish your personal brand, paving the way to more opportunities. Skills Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to:- Apply a learning mindset and take ownership for your own development.
- Appreciate diverse perspectives, needs, and feelings of others.
- Adopt habits to sustain high performance and develop your potential.
- Actively listen, ask questions to check understanding, and clearly express ideas.
- Seek, reflect, act on, and give feedback.
- Gather information from a range of sources to analyse facts and discern patterns.
- Commit to understanding how the business works and building commercial awareness.
- Learn and apply professional and technical standards (e.g. refer to specific PwC tax and audit guidance), uphold the Firm's code of conduct and independence requirements.
- Supporting teams in the development and implementation of AI and machine learning models
- Assisting in the analysis and interpretation of complex data sets to derive actionable insights
- Participating in the design and maintenance of data pipelines and data engineering processes
- Engaging in data modeling and predictive modeling to enhance decision-making processes
- Collaborating with team members to apply data science algorithms and methodologies
- Utilizing programming languages such as C++, R, and MATLAB for data analysis and model development
- Contributing to the development of natural language processing solutions and applications
- Assisting in the integration of big data technologies to improve data processing capabilities
- Learning and applying project management techniques to support project goals and timelines
- Observing and participating in client support activities to gain exposure to industry practices
- Currently pursuing or have completed a Bachelor's degree
- Client service intern positions are entry-level roles intended for job seekers who are in their third year of a four-year degree program or fourth year of a five-year program at the time of application. Winter internships typically occur during the spring semester preceding the student's final year of school Summer internships typically take place during the summer preceding the student's final year of school
- Preference for one of the following field(s) of study: Artificial Intelligence and Robotics, Business Analytics, Computer and Information Science, Computer Engineering, Computer Programming, Data Processing/Analytics/Science, Engineering, Mathematics, Statistics, Systems Engineering
- Preference for a 3.3 overall GPA
- Demonstrating proficiency in C++ and R programming languages
- Applying knowledge of machine learning and data modeling techniques
- Utilizing Scikit-Learn for machine learning projects
- Engaging in complex data analysis and predictive modeling
- Supporting data-driven decision-making processes
- Participating in natural language processing initiatives
- Leveraging AI to create efficiencies, innovate ways of working and deliver distinctive outcomes
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