Senior Data Scientist
A
AwinData science
Location: Amsterdam, North Holland, Netherlands; Berlin, Berlin, Germany; Hannover, Lower Saxony, Germany; Iași, Iași, Romania; London, England, United Kingdom; Madrid, Madrid, Spain; Manchester, England, United Kingdom; Milano, Milan, Italy; München, Bavaria, Germany; Warsaw, Masovian Voivodeship, PolandFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 5+ years of experience working as a Data Scientist, Machine Learning Engineer, Applied Scientist, or similar role.
- Required Skills
- PythonMachine LearningMLFlowNumpyPyTorchTensorflowDatabricksscikit-learnPySpark
Requirements
- Have 5+ years of experience as a Data Scientist, Machine Learning Engineer, Applied Scientist, or in a similar role.
- Have proven experience delivering machine learning and analytical solutions from discovery through deployment and business impact.
- Demonstrate advanced proficiency in Python and relevant data science libraries, including NumPy, PySpark, Scikit-learn, TensorFlow, and/or PyTorch.
- Have strong experience using Databricks, including Jobs, Asset Bundles, Delta Lake, and MLflow.
- Have experience working with business stakeholders to define problems, scope solutions, and communicate outcomes.
- Have experience mentoring data scientists or providing technical leadership within a cross-functional team.
- Hold a bachelor's degree or higher in Statistics, Mathematics, Computer Science, Data Science, Engineering, or a related quantitative discipline.
- Have expertise in machine learning and predictive modelling, including production delivery.
- Be able to evaluate and refine models using experimentation, performance metrics, and business outcomes.
Responsibilities
- Lead development and deployment of machine learning, forecasting, recommendation, and analytical solutions.
- Partner with Product, Commercial, Engineering, and Data stakeholders to identify opportunities and translate business challenges into data-driven solutions.
- Design evaluation frameworks, experiments, and success metrics to measure performance and business outcomes.
- Apply statistical modelling, machine learning, and advanced analytical techniques to solve business problems.
- Build feature engineering, model development, and deployment workflows with Data Engineering and Software Engineering teams.
- Drive rapid MVP development while ensuring a path to sustainable production solutions.
- Define and promote best practices for model development, evaluation, monitoring, and governance.
- Mentor and support other data scientists and contribute to team knowledge sharing.
- Communicate findings, recommendations, and technical concepts to technical and non-technical audiences.
- Contribute to the Data Science roadmap and identify opportunities to apply advanced analytics and machine learning.
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