The Role
Design, develop, and deploy end-to-end machine learning solutions. Build scalable data pipelines and analytics using Python and SQL, develop statistical and predictive models, work with cloud ML platforms (Azure, AWS, GCP), optimize model performance, and collaborate with cross-functional teams to productionize and maintain ML systems.
Summary Generated by Built In
As a Senior Machine Learning Engineer, you will:
- Design, develop, and deploy machine learning solutions to solve complex business problems.
- Build scalable data processing and analytics solutions using Python and SQL.
- Develop statistical and machine learning models to support predictive analytics and data-driven decision-making.
- Analyze, clean, and transform structured and unstructured datasets for model development.
- Work with cloud-based analytics and machine learning platforms, including Azure Machine Learning Studio, Azure Databricks, AWS, and Google Cloud Platform (GCP).
- Collaborate with cross-functional teams to understand business requirements and translate them into scalable AI and data science solutions.
- Optimize model performance through feature engineering, model evaluation, and continuous improvement.
- Develop reusable data science workflows and maintain high standards for code quality and documentation.
- Support deployment, monitoring, and maintenance of machine learning solutions in cloud environments.
- Stay updated with emerging technologies and best practices in machine learning, cloud computing, and data engineering.
What You Bring to the Table:
- 8–10 years of professional experience in Python development, Data Science, Machine Learning, or Analytics Engineering.
- Strong programming expertise in Python with hands-on experience using Scikit-learn, Pandas, NumPy, Matplotlib, statsmodels, and related data science libraries.
- Working knowledge of R for statistical computing and data analysis.
- Strong SQL skills with experience working on enterprise data platforms such as Teradata and BigQuery.
- Solid understanding of machine learning algorithms, model training, validation, and evaluation techniques.
- Experience in statistical analysis, predictive modeling, and data exploration.
- Familiarity with cloud-based analytics and machine learning platforms, including Azure Machine Learning Studio, Azure Databricks, Google Cloud Platform (GCP), and Amazon Web Services (AWS).
- Experience working with large datasets and designing scalable analytics solutions.
- Strong analytical, problem-solving, and communication skills.
- Ability to quickly learn new technologies and adapt to evolving business requirements.
You Should Possess the Ability to:
- Design and implement end-to-end machine learning solutions.
- Develop scalable data processing pipelines and analytical models.
- Apply statistical techniques to extract meaningful business insights.
- Build, evaluate, and optimize machine learning models using industry best practices.
- Work with cloud-native machine learning and analytics platforms.
- Analyze large and complex datasets using SQL and Python.
- Collaborate effectively with data engineers, analysts, architects, and business stakeholders.
- Troubleshoot technical issues and optimize model performance.
- Communicate technical concepts clearly to both technical and non-technical audiences.
- Deliver high-quality solutions while maintaining a strong focus on accuracy, scalability, and continuous improvement.
What We Bring to the Table:
- Opportunity to work on enterprise-scale data science and machine learning initiatives.
- Exposure to modern cloud platforms, advanced analytics, and AI technologies.
- A collaborative environment focused on innovation, continuous learning, and technical excellence.
- Opportunities to work with experienced engineers, data scientists, and cloud architects.
- Challenging projects involving Python, cloud-native machine learning, statistical modeling, and enterprise analytics.
- A culture that encourages ownership, knowledge sharing, and professional growth.
- Continuous opportunities to enhance expertise in cloud computing, machine learning, and advanced data engineering.
Let’s Connect
Want to discuss this opportunity in more detail? Feel free to reach out.
Recruiter: Giftson Paul Davidson
Phone: +31 20 369 0609 ; Extn : 151
LinkedIn: https://www.linkedin.com/in/giftsonpauldavidson/
Skills Required
- 8-10 years professional experience in Python development, Data Science, Machine Learning, or Analytics Engineering
- Strong programming expertise in Python with hands-on experience using Scikit-learn, Pandas, NumPy, Matplotlib, statsmodels
- Working knowledge of R for statistical computing and data analysis
- Strong SQL skills with experience working on enterprise data platforms such as Teradata and BigQuery
- Solid understanding of machine learning algorithms, model training, validation, and evaluation techniques
- Experience in statistical analysis, predictive modeling, and data exploration
- Familiarity with cloud-based analytics and ML platforms (Azure Machine Learning Studio, Azure Databricks, GCP, AWS)
- Experience working with large datasets and designing scalable analytics solutions
- Strong analytical, problem-solving, and communication skills
- Ability to quickly learn new technologies and adapt to evolving business requirements
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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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