Senior Data Scientist (Romania Based)

We are looking for a highly skilled Senior Data Scientist to join our team in Romania. In this role, you will lead advanced analytics projects, develop predictive and prescriptive models, and transform data into actionable insights that drive strategic decisions. You will collaborate closely with business stakeholders, data engineers, and product teams to deliver scalable data science solutions across the organization.

Key Responsibilities

• Design, develop, and deploy advanced machine learning models and statistical solutions.
• Translate complex business problems into analytical projects with measurable impact.
• Work with large, structured and unstructured datasets to extract insights and identify opportunities.
• Partner with data engineering teams to ensure high-quality, scalable data pipelines and model deployment.
• Communicate findings and recommendations to non-technical stakeholders in a clear, actionable way.
• Mentor junior data scientists and contribute to best practices in model development, validation, and monitoring.
• Stay updated on emerging trends in machine learning, AI, and data science technologies.

Qualifications & Skills

• Bachelor’s or Master’s degree in Data Science, Computer Science, Mathematics, Statistics, or related field (PhD preferred).
• 5+ years of hands-on experience as a Data Scientist.
• Strong expertise in Python (pandas, scikit-learn, TensorFlow, PyTorch) or R.
• Proficiency in statistical modeling, machine learning, and data visualization techniques.
• Experience with SQL and working knowledge of relational and NoSQL databases.
• Familiarity with cloud platforms (AWS, Azure, or GCP) and MLOps practices.
• Strong understanding of data structures, algorithms, and software engineering principles.
• Excellent problem-solving skills and ability to work with cross-functional teams.
• Strong communication and presentation skills in English.

Nice to Have

• Experience with big data tools (Spark, Hadoop).
• Familiarity with deep learning and NLP techniques.
• Knowledge of A/B testing and experimentation frameworks.
• Exposure to productionizing models with Docker, Kubernetes, or similar tools.