Data Science and Machine Learning Engineering Analyst

Job Description

Are you passionate about transforming raw data into actionable insights and contributing to innovative solutions? Will you take on the challenge to help our clients become data-driven? Do you want to change the way organizations manage their data and do business? Are you interested in how data flows through an organization and how it is governed to generate knowledge and value? Do you enjoy working at the forefront of the latest Advanced AI developments and applying them directly to create tangible client value? If so, we invite you to explore a role as a Data Science and Machine Learning Engineering Analyst (Data Science Analyst) at Accenture.

The work

As a Data Science Analyst, you will be joining our Data & AI team. You will work directly with various clients, located in both The Netherlands and abroad, on new problem-solving solutions and methodologies, data modelling, analyses & interpretation. You apply the latest algorithms and techniques such as Machine Learning, Deep Learning, Generative and Agentic AI to create value for action. Examples include building recommender systems that increase customer loyalty, predicting risk at an individual level to better comply with rules and regulations, developing GenAI-powered applications or intelligent agents that support decision-making or automate processes, and creating NLP solutions (including sentiment analysis) to increase efficiency.

You have strong technical skills and are also able to facilitate workshops/interviews to bridge the gap between data analytics and business outcomes. You collaborate with cross-functional teams to address real-world business problems. You provide advice to clients by translating analytical solutions into recommendations. You help to achieve strategic goals and impact business results.

• People Engage collaboratively with clients to comprehend their data-oriented challenges, deliver insights, and suggest data-driven solutions aligned with their organizational goals. Establish enduring relationships with vital stakeholders to foster long-term partnerships and facilitate seamless collaboration. Develop Proof-of-Concepts aimed at illustrating potential data science solutions to clients, showcasing the inherent value of employing data-driven methodologies.
• Processes Analyze extensive and intricate datasets, performing data cleansing, preprocessing, and data transformation into formats suitable for diverse data science applications. Apply a diverse array of data science techniques, encompassing statistical modeling and machine learning algorithms, to extract insights and provide resolutions to business inquiries.
• Technology and Data Collaborate closely with cloud platforms (Microsoft Azure / AWS / GCP, etc.) to deploy and manage production-ready models, ensuring both scalability and operational efficiency.

With all our roles, there is in-person time for collaboration, learning and building relationships with clients, peers, leaders, and communities. As an employer, we will be as flexible as possible to support your specific work/life needs.