Data Science and Machine Learning Engineering Analyst
Role details
Job location
Tech stack
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 the role of a 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.
Requirements
- 0 to 3 years of professional experience in data analysis using statistical modeling and machine learning techniques to solve business questions.
- Master's degree (WO) in a quantitative field (Data Science, Mathematics, Computer Science, Econometrics, Business Analytics or any other relevant studies) with specific emphasis on data
- Experience with relevant programming languages (SQL, Python, R, etc.), Machine Learning techniques (Neural Networks, Random Forest, etc.), Cloud computing (AWS, Azure or GCP) and ML & Agentic AI frameworks (Langchain, LangGraph, PyTorch, Tenserflow, etc.).
- Basic experience with data visualization tools such as Power BI, Tableau, Qlik, matplotlib, seaborn etc.
- English (Dutch proficiency is a plus)
- Excellent problem-solving skills and the ability to tackle complex challenges.
- Effective communication skills to convey insights to technical and non-technical stakeholders.
Bonus points if you have
- Hands-on experience with building Generative or Agentic AI applications, for example using frameworks or tooling such as LangGraph, Google ADK, or similar orchestration frameworks.
- Participated in extracurricular activities such as student consulting clubs, board roles, internships that showcase your leadership skills.
- Proven affinity with data and a strong analytical mindset.
- Demonstrated stakeholder management activities and familiarity with using AI, data science, and machine learning to achieve business goals.
Benefits & conditions
These promises are reflected through our excellent employee benefits, including:
- Unlimited learning: access to thousands of free courses, classes and workshops.
- Flexible working hours (4x9) & work location.
- Paid transport (budget for electric bicycle or car, NS-Business card).
- Parental leave, Paternity leave for all non-birthing parents.
- Pension scheme, discount on Accenture shares, annual bonus, collective health insurance scheme.