Senior Data Scientist

Line of Service: Assurance

Industry/Sector: Not Applicable

Specialism: Risk Architecture

Management Level: Senior Associate

Job Description & Summary:

A career within Assurance Support Services will provide the opportunity to support our engagement teams and clients by providing advice and counsel on accounting, financial reporting, and strategic business issues. In joining, you’ll help ensure a complete and relevant exchange of information among our consultants and in turn with engagement teams and clients, provide expert advice on a variety of specific topics, support engagement teams in resolving complex issues, and support clients and their subsidiaries in evaluating the potential impact of accounting and reporting standard setting initiatives. You’ll develop strong relationships with our engagement teams and established audit clients and enhance our ability to meet greater investor expectations with the challenges of an increasingly complex business environment.

Our team works closely with engagement teams, PwC leadership, PwC counsel, and other groups within PwC to identify and manage practice matters. You’ll play an integral role in developing policy, processes, and tools to support the assurance practice and will interact daily with engagement teams to help staff navigate the challenging and highly judgmental aspects of the audit practice.

As a Senior Associate, you'll work as part of a team of problem solvers, helping to solve complex business issues from strategy to execution. PwC Professional skills and responsibilities for this management level include but are not limited to:

• Use feedback and reflection to develop self-awareness, personal strengths, and address development areas.
• Delegate to others to provide stretch opportunities, coaching them to deliver results.
• Demonstrate critical thinking and the ability to bring order to unstructured problems.
• Use a broad range of tools and techniques to extract insights from current industry or sector trends.
• Review your work and that of others for quality, accuracy, and relevance.
• Know how and when to use tools available for a given situation and can explain the reasons for this choice.
• Seek and embrace opportunities which give exposure to different situations, environments, and perspectives.
• Use straightforward communication, in a structured way, when influencing and connecting with others.
• Able to read situations and modify behavior to build quality relationships.
• Uphold the firm's code of ethics and business conduct.

Key Responsibilities:

• Analyze large and complex datasets to identify patterns and trends using statistical techniques to derive actionable insights.
• Develop, test, and validate predictive and descriptive models to support business objectives. Apply machine learning algorithms and statistical methods to solve real-world problems.
• Create clear and compelling visualizations to communicate findings and insights to stakeholders.
• Clean, preprocess, and transform data from various sources to ensure accuracy and usability for analysis and modeling.
• Generate and present reports that summarize analytical findings and recommendations. Provide actionable insights to guide strategic decision-making.
• Stay abreast of the latest trends and advancements in data science, machine learning, and analytics. Propose and implement innovative techniques and methodologies to enhance data practices.
• Maintain thorough documentation of data science processes, models, and methodologies to ensure transparency and reproducibility.

Experience and Qualifications:

• Bachelor’s Degree in Data Science, Computer Science, Statistics, Mathematics, or a similar field.
• Minimum 2-3 years of experience as a Data Scientist or in a similar role, with a proven track record of applying data science techniques to drive business outcomes.
• Proficient in data analysis and visualization tools (e.g., Python, R, SQL, Tableau, Power BI). Experience with machine learning libraries and frameworks (e.g., TensorFlow, PyTorch).
• Proficient in cloud platforms (e.g., AWS Sagemaker, AWS Quicksight, Azure Machine Learning).
• Experience with deep learning techniques and natural language processing (NLP).
• Excellent analytical and problem-solving skills with the ability to tackle complex data challenges and derive actionable insights.
• Strong verbal and written communication skills, with the ability to present complex findings in a clear and concise manner.
• Knowledge of data privacy and security best practices.

Travel Requirements: Up to 40%

Government Clearance Required: Yes