Data Scientist
Description
Damia supports its clients with direct hires.
- Data Exploration and Preprocessing: Collect, clean, and transform large, complex data sets from various sources to ensure data quality and integrity for analysis
- Statistical Analysis and Modeling: Apply statistical methods and mathematical models to identify patterns, trends, and relationships in data sets, and develop predictive models
- Machine Learning: Develop and implement machine learning algorithms, such as classification, regression, clustering, and deep learning, to solve business problems and improve processes
- Feature Engineering: Extract relevant features from structured and unstructured data sources, and design and engineer new features to enhance model performance
- Model Development and Evaluation: Build, train, and optimize machine learning models using state-of-the-art techniques, and evaluate model performance using appropriate metrics
- Data Visualization: Present complex analysis results in a clear and concise manner using data visualization techniques, and communicate insights to stakeholders effectively
- Collaborative Problem-Solving: Collaborate with cross-functional teams, including product managers, data engineers, software developers, and business stakeholders to identify data-driven solutions and implement them in production environments
- Research and Innovation: Stay up to date with the latest advancements in data science, machine learning, and related fields, and proactively explore new approaches to enhance the company's analytical capabilities
- B.Sc (M.Sc is a plus) in Computer Science, Mathematics, Statistics, or a related field
- 3+ years of proven experience designing and implementing machine learning algorithms and successfully deploying them to production.
- Strong understanding and practical experience with various machine learning algorithms.
- Proficiency in Python
- Experience with SQL and data manipulation tools (e.g., Pandas, NumPy) to extract, clean, and transform data for analysis
- Solid foundation in statistical concepts and techniques, including hypothesis testing, regression analysis, time series analysis, and experimental design
- Strong analytical and critical thinking skills to approach business problems, formulate hypotheses, and translate them into actionable solutions
- Proficiency in data visualization libraries to create meaningful visual representations of complex data
- Excellent written and verbal communication skills to present complex findings and technical concepts to both technical and non-technical stakeholders
- Demonstrated ability to work effectively in cross-functional teams, collaborate with colleagues, and contribute to a positive work environment
- Experience with Big Data tools
- Currently living in Portugal and legally authorized to work in the country
- Experience in the fraud domain
- Experience with Airflow, CircleCI, PySpark, Docker and K8S
