Data cleaning and processing: Perform data cleaning, transformation, and integration to prepare structured data for analysis and modelling
Data pipeline maintenance: Maintain and update data pipelines and infrastructure components to support model deployment and data flow.
Model and data reliability: Conduct reliability checks on data and model outputs to ensure consistency and accuracy across all projects.
Technical growth: Take ownership of personal development by working on complex projects and actively seeking feedback from senior team members.
Data analysis execution: Analyse structured and unstructured data sets to identify patterns and generate actionable insights using analytical techniques.
Predictive model development: Develop predictive models using standard algorithms and validate model performance for specific business scenarios.
Hypothesis testing execution: Design and conduct hypothesis testing using A/B testing methods, ensuring accurate interpretation of results.
Data visualization creation: Create clear and informative data visualizations using industry-standard tools to communicate key findings.
Feature engineering implementation: Implement feature engineering techniques to optimize model performance and ensure predictive reliability.
Model evaluation and improvement: Evaluate model performance and refine the model iteratively to improve predictive accuracy.
Project collaboration: Collaborate with team members and other departments to ensure smooth execution of data-centric projects.
Comprehensive documentation: Maintain meticulous documentation of best practices, methodologies, data lineage, model development, and analytical findings to ensure transparency and reproducibility
Continuous learning: Remain at the vanguard of data science by keeping abreast of emerging technologies, methodologies, and industry best practices
Desired Experience and Qualifications
Bachelor's degree or above in computer science, computer engineering, information technology, statistics, mathematics, business analytics or a related quantitative field
3+ years of experience in data science or a related analytical field.
Experience applying software engineering methodologies and best practices including coding standards, code reviews, build processes, testing, and security.
Prior experience in developing AI solutions on public cloud services is an advantage.
