The Role
Develop and maintain production-ready machine learning models to detect periodic patterns in large transactional datasets. Design features, optimize algorithms, expand time-related features, and participate across the full MLOps lifecycle. Collaborate with data scientists, ML engineers, analysts, and stakeholders to deliver scalable, architecture-aligned analytical solutions and communicate technical insights to business audiences.
Summary Generated by Built In
As a Data Scientist, you will:
- 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.
Recruiter: Asha Krishnan
Phone: +31 20 369 0609 ; Extn :146
LinkedIn:https://www.linkedin.com/in/asha-krishnan
Skills Required
- Solid experience working with large datasets and advanced analytics or machine learning techniques
- Strong programming expertise in Python
- Experience working with PySpark for large-scale data processing
- Practical experience using Git for version control and collaborative development
- Experience building, evaluating, and optimizing predictive models and advanced analytics solutions
- Familiarity with time series analysis, forecasting models, or periodic pattern detection techniques
- Experience delivering production-ready code as part of an end-to-end ML development team
- Ability to work across the entire MLOps lifecycle including development, deployment, monitoring, and optimization
- Strong analytical thinking and business-oriented mindset
- Excellent collaboration and communication skills
- Experience with Databricks
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The Company
What We Do
STAFIDE is a Netherlands-based niche technology talent consulting company operating across Europe. It helps organizations identify, recruit, and deploy technology professionals in areas including cybersecurity, cloud engineering, software development, data analytics, ERP, infrastructure, and digital transformation. Its services include recruitment, workforce engagement, secondment, onboarding support, workforce deployment, and workforce analytics that support technology hiring and expansion.
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