ETIC, Data science -Associate

4 Months ago β€’ All levels β€’ Data Analyst

Job Summary

Job Description

Job Details

Line of Service

Advisory

Industry/Sector

Technology

Specialism

Advisory - Other

Management Level

Associate

Job Description & Summary

In an increasingly digitised world, instances of fraud and electronic crime are becoming more and more common. Investigative Analytics involves the analysis of data to support forensic investigations. Much of our work requires us to analyse vast quantities of data, using cutting edge technology and advanced statistical techniques to extract meaningful insights for our worldwide clients. Because we operate in an environment where speed of response is often critical to our clients, we are constantly innovating and drawing on the very latest technologies.

The very nature of what we do means that many of our clients have an international reach, and no two jobs, or indeed days, are the same. So, if you are naturally inquisitive, have an analytical mind and enjoy solving problems in a rigorous and methodological manner, we’d be interested in talking to you.

Your responsibilities will include but may not be limited to:

  • Building and maintaining in-depth understanding of machine learning concepts across all areas, in particular; supervised, unsupervised, reinforcement learning and large language models.

  • Writing Python / R code to create, tune and validate models.

  • Writing SQL / Python code as part of forensic investigations to identify fraud, error and non-compliance in large, structured data sets.

  • Optimising code and infrastructure for machine learning performance.

  • Consulting with clients on business issues, often explaining complex technical concepts to non-technical people.

  • Creation of novel visualisations and explanations to demonstrate our work.

  • Developing new propositions to take to our clients.

  • Researching new products, tools and techniques to assist with advancing our machine learning and data science capability.

Technical Skills:

  • 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 the effect they have on machine learning models;

  • Data cleansing and manipulation for forensic investigations and machine learning (e.g. feature engineering);

  • Dimensionality reduction techniques (e.g. principal component analysis);

  • Hyperparameter optimization approaches for a range of models;

  • Data visualisation tools (e.g. Power BI)

  • Use of Large language models for natural language processing;

  • Experience with financial / general ledger data;

  • Knowledge of the current data science software platforms;

  • Knowledge of Generative AI and concepts such as retrieval augmented generation.

Soft Skills:

  • The ability to come up with creative solutions to complex problems;

  • Exceptional analytical and technical aptitude;

  • Exceptional attention to detail;

  • The ability to manage time, prioritise tasks and work under tight deadlines;

  • The ability to work independently with little supervision, but integrate well into teams;

  • Concise and clear communication when presenting and explaining results and findings.

  • Naturally inquisitive

  • Analytical mindset

Education (if blank, degree and/or field of study not specified)

Degrees/Field of Study required:

Degrees/Field of Study preferred:

Certifications (if blank, certifications not specified)

Required Skills

Optional Skills

Desired Languages (If blank, desired languages not specified)

Travel Requirements

Available for Work Visa Sponsorship?

Government Clearance Required?

Job Posting End Date

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About The Company

At PwC, our purpose is to build trust in society and solve important problems. We’re a network of firms in 152 countries with over 327,000 people who are committed to delivering quality in assurance, advisory and tax services. Find out more and tell us what matters to you by visiting us at www.pwc.com. PwC refers to the PwC network and/or one or more of its member firms, each of which is a separate legal entity.


Content on this page has been prepared for general information only and is not intended to be relied upon as accounting, tax or professional advice. Please reach out to your advisors for specific advice.

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