Senior Data Scientist-Romania

We are looking for a Senior Data Scientist to join our client's data and analytics team. The ideal candidate will have strong experience in machine learning, statistical analysis, data modeling, and Python, with the ability to transform complex datasets into actionable insights and scalable data-driven solutions.
You will work closely with Data Engineers, Software Engineers, Product Managers, and business stakeholders to develop, deploy, and continuously improve machine learning models and analytical solutions.
Key Responsibilities
Develop, train, validate, and deploy machine learning models for business and technical use cases.
Analyze large and complex datasets to identify patterns, trends, correlations, and business opportunities.
Design and implement statistical and predictive models.
Perform exploratory data analysis (EDA) and feature engineering.
Develop and optimize machine learning algorithms and data science pipelines.
Evaluate model performance using appropriate metrics and validation techniques.
Collaborate with Data Engineers to build reliable and scalable data pipelines.
Deploy and monitor machine learning models in production environments.
Improve existing models through experimentation, tuning, and continuous evaluation.
Translate business requirements into data science solutions and measurable outcomes.
Communicate technical findings and model results clearly to both technical and non-technical stakeholders.
Contribute to data science best practices, documentation, and code quality standards.
Stay up to date with the latest developments in AI, Machine Learning, Generative AI, and data science.
Must-Have Skills
5+ years of professional experience in Data Science, Machine Learning, or a related field.
Strong programming skills in Python.
Strong knowledge of Machine Learning concepts and algorithms.
Experience with libraries and frameworks such as Pandas, NumPy, Scikit-learn, and similar tools.
Strong understanding of statistics, probability, and predictive modeling.
Experience with SQL and relational databases.
Hands-on experience with data preprocessing, feature engineering, model training, and evaluation.
Experience working with large and complex datasets.
Understanding of MLOps principles and machine learning model lifecycle management.
Experience with data visualization tools such as Power BI, Tableau, Matplotlib, or similar.
Good understanding of software engineering practices, including Git, testing, and clean code.
Strong analytical and problem-solving skills.
Good command of English.
Nice to Have
Experience with Deep Learning and frameworks such as TensorFlow or PyTorch.
Experience with Generative AI, LLMs, RAG, embeddings, and vector databases.
Knowledge of Natural Language Processing (NLP) or Computer Vision.
Experience with cloud platforms such as Azure, AWS, or GCP.
Experience with Databricks, Spark, or PySpark.
Knowledge of ML platforms and tools such as MLflow, Kubeflow, or SageMaker.
Experience with Docker and Kubernetes.
Experience building and deploying AI/ML solutions in production.
Knowledge of CI/CD and automated deployment practices.
Soft Skills
Strong analytical and critical-thinking abilities.
Excellent problem-solving and decision-making skills.
Ability to work independently and take ownership of projects.
Strong communication and presentation skills.
Ability to explain complex technical concepts to non-technical stakeholders.
Collaborative and proactive mindset.
Strong attention to detail and focus on delivering business value.

Work arrangement
Yes