Data Scientist-ROMANIA BASED

We are looking for a highly skilled Data Scientist to join our analytics team and help drive data-informed decision making across the organization. The ideal candidate will have strong analytical, statistical, and programming skills, with the ability to transform complex data into actionable insights that support strategic and operational goals.

Key Responsibilities

• Collect, process, and analyze large datasets from multiple sources to extract valuable insights.
• Develop predictive models and machine learning algorithms to address business challenges.
• Apply statistical and mathematical techniques to identify trends, patterns, and anomalies in data.
• Collaborate with cross-functional teams (engineering, product, operations, business) to define analytical problems and deliver data-driven solutions.
• Communicate findings and recommendations clearly through dashboards, visualizations, and presentations.
• Build, validate, and maintain data pipelines and model deployment workflows.
• Ensure data quality, reproducibility, and compliance with data governance standards.
• Stay up to date with emerging technologies and best practices in data science, machine learning, and AI.

Required Skills & Qualifications

• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or related field.
• 3+ years of experience working as a Data Scientist or in a similar analytical role.
• Strong proficiency in Python (pandas, scikit-learn, NumPy) or R.
• Experience with SQL and working knowledge of relational and non-relational databases.
• Solid understanding of machine learning algorithms, statistical modeling, and data preprocessing techniques.
• Hands-on experience with data visualization tools (Power BI, Tableau, matplotlib, seaborn, or similar).
• Familiarity with cloud platforms (AWS, Azure, or GCP) and MLOps frameworks.
• Excellent problem-solving and critical-thinking abilities.
• Strong communication skills — able to translate complex analyses into clear business insights.

Preferred Qualifications

• Experience with deep learning frameworks (TensorFlow, PyTorch).
• Knowledge of big data technologies (Spark, Databricks, Hadoop).
• Experience deploying models into production (using APIs, Docker, or CI/CD pipelines).
• Background in time-series forecasting, NLP, or computer vision.
• PhD in a quantitative field is a plus.