PwC Is Hiring Data Analyst

Qualifications

To be considered you must be able to demonstrate experience working in a data analysis/ data science role, covering multiple of the following disciplines:

• Data transformation and modelling (e.g. pandas and scikit-learn in Python);
• Data storage and querying (e.g. SQL);
• Understanding of common data quality issues and they effect they have on machine learning models;
• Data cleansing and manipulation for machine learning (e.g. feature enginee ing);
• Data Visualization (e.g PowerBi, Tableau)
• Experience with financial / general ledger data;
• Knowledge of the current data science software platforms.

To be successful in this role you will need to demonstrate the following:

• The ability to devise creative solutions to complex problems;
• Exceptional analytical and technical aptitude;
• Meticulous attention to detail;
• Strong time management skills, including the ability to prioritise tasks and work under tight deadlines;
• The capability to work independently with minimal supervision, while integrating well into teams;
• Strong writing and presentation skills;
• Concise and clear communication when presenting and explaining results and findings.
• Possess a deep understanding of machine learning concepts, with a particular focus on supervised, unsupervised, and reinforcement learning.
• Optimise code and infrastructure to enhance machine learning performance.

Outstanding potential takes many forms and academic success is just one measure. That’s why we have our ‘Outstanding Achievement’ entry route – it’s an innovative way we’re able to support applications from people who may not have met the academic requirements we’re looking for, but have excelled in something else.

Your responsibilities will include but may not be limited to:

• Demonstrate aptitude for conducting quantitative and qualitative analyses of large and complex data as it relates to the project requirements;
• Write Python / R code to create, tune and validate models.
• Utilise SQL code for data interrogation and investigations;
• Consult with clients on business issues, explaining complex technical concepts to non-technical stakeholders.
• Develop novel visualisations and explanations to effectively demonstrate work.
• Exhibit excellent communication skills by accurately interpreting client business needs into technical requirements, performing necessary analyses, and translating findings into actionable business insights.
• Research new products, tools and techniques to assist with advancing our machine learning and data science capability.