PricewaterhouseCoopers-posted 2 months ago
$77,000 - $202,000/Yr
Full-time • Mid Level
New York, NY
Professional, Scientific, and Technical Services

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.

  • Mentor junior team members to enhance their skills and knowledge
  • Refine machine learning models and generative AI applications
  • Utilize cloud platforms such as AWS, Azure, or Google Cloud for project execution
  • Stay updated on industry trends and emerging technologies
  • Bachelor's Degree
  • At least 3 years of experience
  • Master's Degree in Computer Science, Data Processing/Analytics/Science, Statistics preferred
  • Certification in Microsoft Copilot preferred
  • Demonstrating proficiency in machine learning and generative AI
  • Utilizing Python for data-driven solutions
  • Leveraging cloud platforms like AWS, Azure, or Google Cloud
  • Analyzing complex business challenges in Financial Services Risk and Regulatory
  • Designing and optimizing AI-driven solutions
  • Having experience with data processing and analysis tools (e.g., Pandas, NumPy, SQL)
  • Being proficient in Python and ML libraries (e.g., Sci-KitLearn, TensorFlow, PyTorch)
  • Possessing a thorough understanding of data structures, algorithms, and statistical methods
  • Rapidly translate business requirements into working prototypes and deployable apps using modern full stack frameworks (e.g., Next.js, Material UI, React)
  • Confidently wire up front-end interfaces with backend APIs, databases, and cloud services to deliver functional end-to-end solutions with minimal handoff
  • Medical
  • Dental
  • Vision
  • 401k
  • Holiday pay
  • Vacation
  • Personal and family sick leave
  • Annual discretionary bonus
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