Key Responsibilities :

Perform machine learning / big data activities:

• Preparation: Data quality assessment, exploration and profiling, design and development of analytic data sets.
• Analysis: Use data analysis tools to drive insights from big-data data sets.
• Modelling: Statistical analysis and machine learning modelling, application of new types of algorithms for predictive modelling, segmentation, forecasting, and optimization.
• Evolve models: Supervise the production of new algorithms into operational processes, measure the results and improve continuously.
• Prototyping: Rapid prototyping to demonstrate value of Big Data use cases.
• Production: Moving prototypes into production

Database, business analysis, data visualization and development:

• Databases: Build data bases, data models and ETL tools.
• Business Intelligence: Develop specific tools and dashboards, processes and reporting or data visualizations to deliver a high level of service of the solution implemented and measure their impacts on business.
• Development: API development, API integration, working with applications developers in a data capacity.

Interface with the business:

• Business analysis: Perform business analysis task with business owners and stakeholders.
• Present research and insights: generate reports, annotated code, and other projects artifacts to document, archive, and communicate your work and outcomes.
• Solutions for business partners: Perform statistical analyses and "deep dives" into the data.

Maintain and build the data infrastructure:

• Maintenance: Implement, produce and monitor models and solutions.
• Testing: test and take ownership of solutions and models.

Key Requirements/Skills/Experience

• Bachelor’s Degree in a “STEM” major (Science, Technology, Engineering, Mathematics).
• 1-3 years of experience.
• Mandatory skills include good level in Python (incl. pandas), knowledge / experience in implementing machine learning algorithms, Git, SQL.
• Experience with AWS (or Azure equivalent) and native cloud applications, AWS qualifications highly desirable.
• Demonstrated skills at data cleansing, data quality assessment, and using analytics for data assessment.
• Skills in the use of applied analytics, descriptive statistics, and predictive analytics are desirable.
• Knowledge of big data analysis tools and approaches, having the ability to query databases and perform statistical analysis.
• Developer background, API development and integrations highly desirable.
• Being able to work in a fast-paced multidisciplinary environment.
• Being able to advice senior management in clear language about the implications of their work for the organization.
• Rigorous and passionate with data.
• Strong written and verbal communication skills.
• Good spoken and written English.

If you think you have the right profile and are interested in the above opening, please send your updated CV with existing and expected annual income.

For more details about Euler Hermes, please visit our website at www.eulerhermes.com.

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