Senior Data Scientist
Summary
Senior Data Scientist at XM, a fintech company in Limassol, Cyprus. You'll design and deliver ML solutions using Transformers, GNNs, and advanced analytics on large-scale datasets, collaborating cross-functionally to productionize data products. Requires 5+ years experience, Python expertise (Pandas, NumPy, Polars), and strong communication skills.
The Role:
Are you passionate about transforming complex data into intelligent, business-driven solutions? Do you enjoy solving challenging problems, developing cutting-edge machine learning models, and collaborating with highly skilled professionals?
We are looking for a Senior Data Scientist to join our growing Data Science team. In this role, you will play a key part in designing and delivering innovative data products that create measurable business impact. You'll work with large-scale datasets, advanced machine learning techniques, and modern technologies while collaborating with multiple teams, and business stakeholders to bring data-driven solutions into production.
The main responsibilities of the position include:
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Lead the design, development, and delivery of high-impact data science and machine learning solutions.
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Translate complex business challenges into structured analytical approaches and scalable data products.
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Build, evaluate, and optimize advanced machine learning models, ensuring high standards of quality, performance, and reliability.
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Contribute to technical decisions and best practices across the data science lifecycle.
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Review and validate data preparation, feature engineering, model selection, experimentation, and documentation.
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Support the deployment and operationalization of machine learning models in batch and real-time environments.
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Present analytical insights and recommendations to technical and non-technical stakeholders.
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Ensure compliance with data quality, model governance, security, privacy, and responsible AI standards.
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Identify opportunities to leverage data science for automation, forecasting, personalization, optimization, and risk management.
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Collaborate closely with Data Engineers, Machine Learning Engineers, Software Engineers, Product Owners, and business stakeholders to develop production-ready solutions.
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Contribute to improving team processes, technical standards, and project delivery methodologies.
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Support the Lead Data Scientist in defining priorities, roadmaps, and strategic initiatives.
Main requirements:
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University degree in Mathematics, Physics, Engineering, Computer Science, Data Science, or a related field.
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At least 5 years of experience in a similar role.
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Hands-on experience with Python libraries such as Pandas, NumPy, and Polars for data processing and analysis.
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Strong Python programming skills with the ability to write clean, maintainable, and production-ready code.
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Strong knowledge of modern machine learning techniques and advanced architectures, including Transformers and Graph Neural Networks (GNNs).
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Experience with data visualization libraries such as Matplotlib, Seaborn, and Plotly.
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Good knowledge of SQL and statistical analysis.
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Excellent analytical thinking and problem-solving skills.
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High attention to detail and commitment to delivering high-quality solutions.
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Strong communication skills with the ability to explain technical concepts to non-technical audiences.
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Excellent verbal and written communication skills in English.
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A collaborative mindset, curiosity, and a passion for continuous learning.
What would be considered as an advantage:
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Exposure to Natural Language Processing (NLP).
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Experience working with NoSQL databases.
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Knowledge of software engineering best practices.
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Experience working in Unix/Linux environments.
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Basic understanding of AWS services and cloud-based machine learning environments.
Benefit from:
- Attractive remuneration package plus performance related reward
- Private health insurance
- Corporate pension fund
- Intellectually stimulating work environment
- Continuous personal development and international training opportunities
The Hiring Experience: What Awaits You
- Let’s Connect – Intro Chat with Talent Acquisition
- Deep Dive – First Interview with Your Future Team
- Bring It to Life – Role-Specific Take-Home Task
- Final Connection – Final Interview