Data Scientist at Data Edge – Bucharest | Jobyssey

Apply advanced statistical and machine learning techniques to solve complex business challenges and identify opportunities for growth and optimisation.
Design, develop, validate, and deploy predictive models and advanced analytical solutions, ensuring they are robust, scalable, and fit for purpose.
Perform exploratory data analysis, hypothesis testing, customer segmentation, forecasting, and experimentation to generate actionable insights.
Translate complex analytical findings into clear, data-driven recommendations that support business and strategic decision-making.
Partner closely with business stakeholders to understand objectives, define analytical approaches, and ensure solutions address real business needs.
Communicate analytical results through compelling data storytelling, clear visualisations, and executive-level presentations.
Collaborate with Data Engineering, Product, Technology, Marketing, and Business teams to operationalise models and embed data-driven insights into business processes.
Ensure analytical solutions are explainable, reliable, and aligned with business objectives and expected outcomes.
Contribute to the continuous improvement of data science methodologies, tools, processes, and best practices across the organisation.
Stay up to date with emerging developments in data science, machine learning, MLOps, and Generative AI, identifying opportunities to apply new technologies to business use cases.

BSc or MSc in Computer Science, Data Science, Data Engineering, Statistics, Mathematics, or a related quantitative field.
4–6+ years of hands-on experience in Data Science, Data Analytics, Software Engineering, or Data Engineering, with strong exposure to analytical and predictive modelling.
Strong understanding of statistics, experimental design, forecasting, predictive modelling, and machine learning.
Practical experience with machine learning techniques such as regression, decision trees, random forests, gradient boosting, clustering, and classification.
Strong programming skills in Python and/or R, combined with solid SQL capabilities.
Experience working with data visualisation and business intelligence tools such as Power BI and/or Tableau.

Strong ability to translate complex analytical concepts and findings into clear, actionable business recommendations.
Excellent communication, presentation, and data storytelling skills, with the ability to engage both technical and non-technical audiences.
Demonstrated ability to influence decision-making through data-driven insights.
Experience in customer, marketing, commercial, or digital analytics is highly valued.
Strong stakeholder management skills and the ability to build effective relationships across different functions and seniority levels.
Experience working in cross-functional and matrix organisations.

Exposure to MLOps practices and the deployment and monitoring of machine learning models.
Experience with cloud platforms such as Azure, AWS, or GCP.
Experience with Databricks or similar data and AI platforms.
Exposure to Generative AI and its applications in business and analytics.
Experience working with modern data and analytics ecosystems at scale.

Data Scientist

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