Description :

- Extract, clean, and analyse large datasets from multiple sources using SQL and Python/R.

- Build and optimise data scraping pipelines to process large-scale unstructured data.

- Perform statistical analysis and data mining to identify trends, patterns, and anomalies.

- Develop automated workflows for data preparation and transformation.

- Conduct data quality checks and implement validation procedures.

- Build and validate ML models (classification, regression, clustering) using TensorFlow, Keras, and Pandas.

- Apply feature engineering to enhance accuracy and interpretability.

- Execute experiments, apply cross-validation, and benchmark model performance.

- Collaborate on A/B testing frameworks to validate hypotheses.

- Work on predictive analytics for wildfire risk detection and storm damage assessment.

- Translate complex business requirements into data science solutions.

- Develop predictive models and analytical tools that directly support CRIS decision-making.

- Create interactive dashboards and automated reports for stakeholders.

- Document methodologies and maintain clean, production-ready code repositories.

Requirements :

- 4 - 5 years of hands-on experience in data science, analytics, or quantitative research.

- Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, Engineering, or related field.

- Strong programming skills in Python for data analysis and machine learning.

- Proficiency in SQL and experience with relational databases.

- Experience with ML libraries (scikit-learn, pandas, NumPy, Keras, TensorFlow).

- Knowledge of statistical methods (clustering, regression, classification) and experimental design.

- Familiarity with data visualisation tools (matplotlib, seaborn, ggplot2 Tableau, or similar).

- Exposure to cloud platforms (AWS, GCP, Azure) is a plus.

- Proven experience with end-to-end model development (from data exploration to deployment).

- Track record of delivering actionable insights that influenced business decisions.

- Strong analytical and problem-solving skills with attention to detail.