Job Purpose
As an Executive, Data Analytics, your role will be pivotal in supporting data-driven decision-making processes and delivering valuable insights to support strategic initiatives. You will support in implementing Artificial Intelligence / Machine Learning (AI/ML), leveraging on data to enhance advertising strategies, improve ROI, and contribute to the organisational's growth.
Please note that the incumbent will be hired on a 1 + 1 year contract.
Responsibilities
The duties and responsibilities are listed below. The list is not comprehensive and related duties and responsibilities may be assigned from time to time.
1. Data Analysis and Insights:
- Conduct in-depth data analysis to identify trends, patterns, and actionable insights from advertising campaigns.
- Perform a market-based assessment and execute new go-to-market strategies in the field.
2. Campaign Optimization:
- Collaborate with marketing and sales teams to optimize campaign performance through data-driven strategies.
- A/B testing and experimentation to improve ad creative, targeting, and messaging.
- Streamline and drive process improvements for operational excellence
3. Data Visualization:
- Create data marts, visually appealing and informative data visualizations to communicate findings and insights effectively.
- Develop and maintain dashboards and reports to track key performance metrics and provide actionable recommendations.
- Drive end-to-end data projects identify issues, gather information from various sources, analyse huge data, interpret patterns and trends, build models, give recommendations, and create insightful automated reports.
4 . Artificial Intelligence / Machine Learning (AI/ML)
- Support and implement machine learning models and algorithms.
- Collect, preprocess, and analyze data to train and evaluate AI models.
- Support the building of predictive models to forecast advertising campaign outcomes and customer behavior.
- Collaborate with data engineers to integrate AI solutions into applications and products.
- Test and validate AI models and algorithms to ensure accuracy and reliability.
5. Data Quality and Integrity:
- Ensure data accuracy and integrity by cleaning, transforming, and validating data from various sources.
- Support data mining and forensic review for completeness & accuracy.
6. Reporting and Documentation:
- Prepare and present regular reports and documentation to internal stakeholders and clients.
- Be a steward of good data practices - robust documentation, process and knowledge sharing.
Qualifications & Work Experience
1. Qualifications:
- Bachelor's degree in a related field such as Statistics, Mathematics, Computer Science, or Marketing Analytics preferred.
- Proven experience as a data analyst or similar role in advertising, research or consulting industry will be beneficial.
- Strong analytical thinking and problem-solving skills.
- Excellent written and verbal communication skills.
- Attention to detail and a commitment to data accuracy.
2. Work Experience:
- Minimum of 1-3 years of relevant work experience in data analysis preferred. Experience in the advertising, research or consulting industry will be a plus.
- Demonstrated experience in leveraging data to drive advertising campaign success.
- Track record of creating actionable insights and contributing to campaign optimization.
- Experience with client-facing roles or presenting data-driven insights to clients is a plus.
Skills
1. Technical Abilities:
- Proficiency in data analysis tools and programming languages (e.g., Python, R, SQL).
- Experience with data preprocessing, feature engineering, and model evaluation.
- Strong experience with data visualization tools (e.g., Tableau, Power BI).
- Knowledge of statistical analysis and modeling techniques.
- Experience with data warehousing and ETL (Extract, Transform and Load) processes.
- Understanding of A/B testing methodologies and experimentation.
- Knowledge of machine learning algorithms is a plus.
2. Team Dynamics Abilities:
- Strong communication skills to effectively convey data insights to both technical and non-technical stakeholders.
- Collaborative mindset to work closely with cross-functional teams such as marketing, advertising, and IT.
- Problem-solving skills to address complex data-related challenges.
- Ability to mentor and provide guidance to junior data analysts.
- Adaptability to work in a dynamic and fast-paced advertising environment.
