AI Engineering/Data Science Intern

Specialty/Competency: Data Science Time Type: Full time Travel Requirements: Up to 80% At PwC, our data and analytics engineering team is at the forefront of leveraging advanced technologies to craft robust data solutions for our clients. We are dedicated to transforming raw data into actionable insights that facilitate informed decision-making and spur business growth. As an intern in Data Science and Machine Learning Engineering, you will harness advanced analytics techniques to draw valuable insights from large datasets, driving data-informed decisions. This could involve developing predictive models, conducting statistical analysis, and creating visual data representations to tackle complex business challenges. Driven by curiosity and a proactive mindset, you will contribute significantly as a member of our team. In our dynamic and fast-paced environment, each assignment offers unique challenges and opportunities for growth. You are encouraged to ask questions, take initiative, and deliver quality work that enhances our clients’ experiences and supports our team's success. Your journey with us will also help in establishing your personal brand and expanding future opportunities. The Opportunity As an AI Engineering/Data Science Intern, you will immerse yourself in the innovative field of data science and machine learning engineering. Engaging with cutting-edge technologies, you will contribute to projects that exploit data to deliver impactful client solutions. This internship is designed to provide you with hands-on experience, participation in diverse projects, and observations of professional environments, allowing you to grow and understand PwC's practices better. Responsibilities • Support data science and machine learning projects by aiding in model development and implementation. • Participate in designing and maintaining data pipelines for smooth data flow and integration. • Engage in complex data analyses to extract valuable insights using quantitative methods. • Assist in applying artificial intelligence and natural language processing techniques to enhance data-driven solutions. • Collaborate with team members on programming tasks to develop machine learning algorithms. • Contribute to creating predictive models that inform decision-making processes. • Assist in evaluating and improving data quality to ensure reliable analytics outcomes. • Observe and learn from experienced professionals to gain insights into data engineering and analytics practices. • Support project management tasks by coordinating activities and tracking progress to achieve project objectives. What You Must Have • Currently pursuing or have completed a Bachelor's degree. • Intern positions are entry-level roles meant for individuals in their third year of a four-year degree program or fourth year of a five-year program at the time of application. Internships typically occur during the summer preceding the student's final academic year. What Sets You Apart • Preferred fields of study include Artificial Intelligence, Data Science, Business Analytics, Computer Science, Engineering, Mathematics, or related fields. • Preferred GPA of 3.3 or higher. • Ability to leverage AI for increased efficiencies and innovative outcomes. • Proficiency in programming languages like Python or R. • Experience applying machine learning techniques to complex data problems. • Utilizing natural language processing for actionable insights. • Engagement in predictive modeling to forecast outcomes. • Support data engineering efforts focused on data quality and integrity. PwC is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex (including pregnancy, sexual orientation, and gender identity), age, disability, genetic information, veteran status, marital or citizenship status, or any other status protected by law. The salary range for this position is: $29.25 - $48.00. Actual compensation will depend on skills, experience, qualifications, and applicable employment laws.