Data Science Manager

Description:

Accenture is a leading global professional services company, providing a broad range of services in strategy and consulting, interactive, technology and operations, with digital capabilities across all of these services. With our thought leadership and culture of innovation, we apply industry expertise, diverse skill sets and next-generation technology to each business challenge.

“Across the globe, one thing is universally true of the people of Accenture: We care deeply about what we do and the impact we have with our clients and with the communities in which we work and live. It is personal to all of us.”-Julie Sweet, Accenture CEO

The Data and AI revolution is changing everything. It’s everywhere-transforming how we work and play. Join Accenture and help transform leading organisations and communities around the world. Accenture Applied Intelligence is driving these exciting changes and bringing them to life across 40 industries in more than 120 countries. The sheer scale of our capabilities and client engagements and the way we collaborate with the ecosystem, operate and deliver value provides an unparalleled opportunity to grow and advance.

Accenture's Fraud, Risk and Financial Crime Analytics Global Centre of Excellence, based in Dublin, Ireland covers the range of Data and AI skills, from Strategy, Data Science, Data Architecture, AI Engineering and Visual Insights. We work with our clients to transform their fraud, risk and financial crimes capabilities through the application of Data and AI.

You'll learn, grow and advance in an innovative culture that thrives on shared success, diverse ways of thinking and enables boundaryless opportunities that can drive your career in new and exciting ways

If you’re looking for a challenging career working in a vibrant environment with access to training and a global network of experts, this could be the for you. As part of our global team, you'll be working with cutting-edge technologies and will have the opportunity to develop a wide range of new skills on the job.

• At the forefront across industries, you’ll create, own and make it a reality for clients looking to apply enterprise solutions to prevent and detect fraud, manage risk, and mitigate against financial crime threats.
• Become an integral part of our CoE and the wider Applied Intelligence team with the credibility, expertise and insight clients depend on.
• You will be working with famous brands and household names across the world!
• Lead, motivate and inspire teams of Data Scientists
• Create bespoke machine learning solutions to model/solve problems and to help develop the team
• Solve challenging business problems using data and analytics as the cornerstones of your solutions
• Understand business requirements and support the development of business cases
• Run discovery analytics to identify new and innovative opportunities
• Partner with developers and engineers to deploy, embed and scale machine learning models to deliver complex/critical projects
• Devise reusable assets, solutions and develop best practices for current and future business problems
• Lead analytical discussions and influence analytical direction of client's teams
• Communicate and provide guidance to senior client leadership and teams
• Contribute data science expertise to new sales activities
• Experience with Fraud, Risk or Financial Crime preferred
• Relevant work experience in data science, machine learning, and business analytics
• Practical data science experience with any of Python, SAS, R, Scala, PySpark or other relevant coding language and data science technologies
• Strong proficiency in databases eg. SQL, ETL, No-SQL, DW, and Big Data technologies
• Knowledge of machine learning modelling techniques and how to fine-tune those models eg. Linear models, Random Forest, XGBoost, Neural Networks, Transformers etc.
• Experienced working with structured and also unstructured data, e.g. Text, images, audio, video, network, etc.
• Experience using specialized machine learning libraries e.g. Fastai, Keras, Tensorflow, pytorch, sci-kit learn, huggingface, etc
• Must demonstrate the capacity of reading, understanding and implementing new techniques in the field of machine learning as they emerge
• Experience of using Cloud technologies eg. AWS, GCP or Azure
• Specialised visualisation techniques eg. D3.js, Seaborn, Power BI etc.
• Strong verbal/written communication & data presentation skills
• Ability to lead large projects and drive through to completion
• Mastery of problem solving and solutioning
• Proven history and background in statistics/maths/macroeconomics
• Willingness to travel for client engagements if required