Top Tech Jobs & Startup Jobs

Leads AI product development and contributes machine learning expertise to client projects. Designs cloud architectures, builds production-grade ML and AI solutions, and scales data science models through optimization, testing, and deployment. Provides technical leadership, mentoring, training, client workshops, and thought leadership through blogs, conferences, and press releases. Requires strong programming, cloud, DevOps, database, and big data experience, plus English and Dutch fluency and willingness to travel.

Delivers data-driven consulting solutions by preparing and analyzing datasets, performing statistical and exploratory analysis, and building automated dashboards and reports with tools such as Python or R, SQL, Excel, and BI platforms. Translates technical findings into clear recommendations for clients and supports stakeholder workshops, data literacy, thought leadership, internal training, and business development. The role requires collaboration with local and international clients and contributes to data science and Generative AI offerings.

Build production-grade machine learning and AI solutions for client projects and internal products. Lead AI product development, make cloud architecture decisions, help data scientists scale models into production, mentor engineers, deliver training, and contribute to conferences, blogs, and client workshops. The role combines technical leadership, consulting, software engineering, cloud infrastructure, and collaboration across international data teams.

Design and lead scalable data architectures, pipelines, cloud and distributed systems for client engagements. Develop data models, integration patterns, CI/CD and DataOps practices, while managing stakeholders, mentoring consultants, supporting business development, and contributing to thought leadership and internal capability development.

Build and maintain data engineering, cloud, and machine learning infrastructure for client projects and internal AI solutions. Responsibilities include cloud architecture across GCP, AWS, and Azure; Docker and Kubernetes orchestration; Python development; CI/CD automation; ETL pipelines in Big Data environments; Infrastructure as Code; application security; and deployment and maintenance of data science platforms.

Senior data science consultant developing machine learning, statistical, optimization, simulation, and big data models for clients. Responsibilities include managing end-to-end projects, client relationships, commercial proposals, publications, professional events, and consultant supervision. The role also contributes to internal training, offer development, and knowledge sharing while delivering expert data and AI solutions across client engagements.

Analyze data to identify business problems, develop statistical and analytical methods, generate actionable insights, and translate advanced analytics into business impact. The role involves collaborating with multidisciplinary consulting teams, presenting findings, conducting client workshops, and making recommendations across business areas. Candidates need strong quantitative skills, Python and another analytical language, data visualization experience, and fluency in English and Dutch.

Lead the development of AI products, contribute machine learning expertise to client projects, design cloud architectures, and build production-grade ML/AI solutions. Guide data scientists in deploying and optimizing models, mentor engineers, deliver training, support business development, and represent the company through workshops, conferences, articles, and events.

Build and maintain cloud-based data engineering and machine learning infrastructure for client projects and internal AI solutions. Responsibilities include cloud architecture, containerization with Docker and Kubernetes, Python development, CI/CD automation, ETL pipeline development, Infrastructure as Code, security implementation, and deployment and maintenance of data science applications across GCP, AWS, and Azure.

Lead client engagements involving advanced analytics, predictive modeling, econometrics, optimization, forecasting, Generative AI, and large language models. Advise senior stakeholders, manage multidisciplinary project teams, mentor colleagues, contribute to internal data science offerings and thought leadership, and support business development through proposals and client relationship development.