Data Scientist (ID: 3562)

Stafide; Utrecht; On-site; EUR 60,000 - 80,000; Full time

Benefits offered by this job

Opportunities for professional growth

Collaboration with experienced professionals

Dynamic and innovative work environment

Job summary

A data science firm located in Utrecht, Netherlands is seeking a skilled data scientist to develop and optimize analytics models. The successful candidate will have a strong background in Python and PySpark, experience with large datasets, and the ability to work across the full MLOps lifecycle. Key responsibilities include enhancing model performance and collaborating with cross-functional teams to deliver impactful solutions. This role offers a dynamic environment focusing on innovation and data-driven decision-making.

Qualifications

• Solid experience working with large datasets and advanced analytics or machine learning techniques.
• Strong programming expertise in Python and experience working with PySpark.
• Familiarity with time series analysis, forecasting models, or periodic pattern detection techniques.

Responsibilities

• Develop, improve, and maintain advanced data science models.
• Enhance model performance by designing new features.
• Collaborate with data scientists and stakeholders to implement solutions.

Skills

Python

PySpark

Large dataset analytics

MLOps

Predictive modeling

Time series analysis

Analytical thinking

Collaboration

Tools

Git

Databricks

Job description

• Develop, improve, and maintain advanced data science models to detect recurring and periodic patterns in large transactional datasets.
• Enhance model performance by designing new features and optimizing algorithms for improved analytical insights.
• Expand and refine time-related features used in periodicity detection and forecasting models.
• Deliver high-quality production-ready code as part of an end-to-end data science and machine learning development team.
• Collaborate closely with data scientists, machine learning engineers, business analysts, and product stakeholders to implement scalable analytical solutions.
• Propose innovative ideas and improvements based on a strong understanding of the organization’s analytics landscape.
• Contribute to the design and evolution of machine learning models through experimentation, validation, and continuous improvement.
• Participate across the full MLOps lifecycle including model development, testing, deployment, monitoring, and optimization.
• Ensure solutions are aligned with architecture standards, IT frameworks, and business objectives.
• Communicate analytical insights and technical findings clearly to both technical and non-technical stakeholders.

What You Bring to the Table:

• Solid experience working with large datasets and advanced analytics or machine learning techniques.
• Strong programming expertise in Python and experience working with PySpark for large-scale data processing.
• Practical experience using Git for version control and collaborative development workflows.
• Experience building, evaluating, and optimizing predictive models and advanced analytics solutions.
• Familiarity with time series analysis, forecasting models, or periodic pattern detection techniques.
• Experience working in modern data science platforms such as Databricks is considered an advantage.
• Strong analytical thinking combined with a practical business-oriented mindset.
• Excellent collaboration and communication skills to work effectively with multidisciplinary teams.

You Should Possess the Ability to:

• Design and optimize machine learning and statistical models for complex data environments.
• Translate business challenges into data-driven analytical solutions.
• Work effectively across the entire MLOps lifecycle from experimentation to production deployment.
• Analyze large-scale datasets and extract meaningful insights that support business decision-making.
• Communicate complex analytical results clearly to business stakeholders.
• Collaborate effectively within cross-functional teams consisting of technical and business experts.
• Manage multiple analytical initiatives while maintaining a strong focus on quality and impact.

What We Bring to the Table:

• The opportunity to work on advanced analytics and machine learning solutions with real-world business impact.
• Collaboration with experienced data scientists, machine learning engineers, and analytics professionals.
• A dynamic and innovation-driven environment focused on data-driven decision making.
• Opportunities to contribute to large-scale analytical initiatives and modern MLOps practices.
• Continuous learning and professional growth within a highly collaborative data science ecosystem.

Let’s Connect

Want to discuss this opportunity in more detail? Feel free to reach out.