Senior Data Scientist
Skills
Data EngineeringCluster AnalysisData AnalysisData AnalyticsData ScienceDatasetsExploratory Data Analysis
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- Significant and demonstrable experience delivering Data Science projects using Python programming language and libraries like NumPy, SciPy, Pandas, MLLib and scikit-learn an IDE such as Jupyter Notebooks
- Analytical tool sets such as Athena and Sagemaker with AWS
- Version control in GitHub or similar
- Proactive, detail oriented with problem-solving and critical-thinking skills
- Excellent communication skills for both technical and non-technical stakeholders
- 5+ years proven experience as a Data Scientist
- BSc in Science, Maths, Computing, etc.
- Experience working with software and data engineering teams to develop, test, deploy and monitor statistical and machine learning models in production
- Experience delivering analytics in a high growth, scale-up environment
Nice to have
- Proactive
- Self-motivated
- Detail oriented
- Excellent problem-solving
- Critical-thinking
Day to day
- Work closely with cross-functional teams, including business analysts, engineers, and decision-makers, to understand business objectives and requirements to scope and deliver data science projects.
- Formulate and test hypotheses, providing actionable recommendations based on analysis results.
- Build predictive models to forecast trends and outcomes, contributing to strategic decision-making.
- Communicate insights effectively through the creation of compelling narratives, data visualisations, reports and dashboards.
- Ensure high levels of data quality by preprocessing and transforming data to prepare it for modelling and analytical activity.
Hiring process
- Initial interview
- Technical assessment
- Final interview