The candidate will function as a Manager specializing in Data and Analytics team. He/She will lead the delivery of data and analytics solutions to a diverse range of clients in various industry sectors, and work with PwC teams both within and outside D&A to develop tailored solutions for clients.
Roles & Responsibilities
• Leading teams and delivery of compliance related projects of varying complexity through projects plans, economics, monitoring and evaluating risks, budgets and delivery of projects in line with required standards.
• Provide compliance advisory and assurance services to clients across all industries in line with evolving data and analytics methodologies, framework and standards.
• Provide recommendations to ultimately improve entity-wide data governance/processes and practices, and aid the development of a sound decision making from data & analytics results within the organisation.
• Develop and implement robust data governance structures, frameworks and policies to support organisations seeking to improve their effectiveness and establish a culture of sound analytics practices.
• Lead risk assessments on data & analytics risk areas.
• Develop, implement and review a controls framework around the organisations compliance processes.
• Develop training materials and facilitate data & analytics training programs.
• Review, analyse and advise on new and evolving data & analytics solutions, and their potential impact/ implications for organisations in various respective sectors.
• Play a key role in people development activities (coaching/ mentoring) for less experienced team members and play a key role in attracting and retaining talent to build the team as the business grows.
• Establish and maintain strong working relationship with existing and potential clients, stakeholders and members of the C-Suite.
• Engage in business development activities and initiatives.
• Develop thought leadership in data & analytics for companies across various industries.
• Promote the Data & Analytics within PwC in order to encourage collaboration and increase internal leads.
• Minimum Degree Required Bachelor’s degree in Engineering, Economics, Statistics, Mathematics, Computer Science, Informatics, Operations Research, or other quantitative disciplines.
• Degree Preferred: Master’s degree or Doctorate Engineering, Economics, Statistics, Mathematics, Computer Science, Informatics, Operations Research, or other quantitative disciplines.
Demonstrates thorough knowledge and/or a proven record of success in the following areas:
• New technology learning and quickly evaluating their technical and commercial viability;
• Machine learning techniques for addressing a variety of problems (e.g. consumer segmentation, revenue forecasting, image classification, etc.)
• Machine learning algorithms (e.g. k-nearest neighbors, random forests, ensemble methods, deep neural networks, etc.) and when it is appropriate to use each technique.
Required Skills & Experience
• Building machine learning models and systems, interpreting their output, and communicating the results;
• Moving models from development to production.
• Data Science – Experience turning complex datasets into valuable insights (using tools such as Python, R, Machine learning).
• Data Engineering – knowledge of big data architectures and best practice engineering processes and tools (such as Hadoop, Map Reduce, Hive).
• Business Intelligence/Visualisation: Experience developing solutions using BI tools (e.g., R-Shiny, Python, Matplotlib, Seaborn, bokeh, etc., PowerBI, Qlik, and Tableau).
• Data warehousing: Strong relational database and data warehousing knowledge (including T-SQL, PL/SQL, NoSQL, Hadoop, cloud-based databases such as GCP BigQuery or similar).
• Data management: Proven capability in the use of ETL and/or Master Data Management solutions (Informatica, MS SQL Server, IBM InfoSphere).
• Team working and leadership: A strong background in collaborative working with other creative and passionate data engineers.
• Data Processing Tools: R(dplyr, etc), Python (Numpy, Pandas, etc.), Spark, etc;
• Experience in building and maintaining strong relationships with C-Level client stakeholders.
• Experience in business development and relationship building.
• Strong analytics, IT skills and technical depth.
• Excellent analytical skills, attention to detail and problem solving skills.
• A proactive approach to problem solving, delivering results and meeting client expectations.
• Excellent written and oral communications skills (presentation & facilitation).
• Project management skills – ability to manage across multiple and complex projects.
• Demonstrable creativity and innovation.