
Data Scientist
- Belfast
- Contract
- Full-time
- Design and analyse experiments (A/B tests, causal inference studies) to measure marketing effectiveness and guide business decisions.
- Apply advanced statistical methodologies (e.g., Instrumental Variables, Synthetic Control, Propensity Score Matching, Market Mix Modelling, Panel & Time-Series Econometrics, Statistical Learning Techniques) to measure the causal impact of marketing, pricing & external factors on key business outcomes.
- Engage with partners across marketing, Customer Analytics, GWS, Product Teams and external agencies to find opportunities to enhance web analytics or marketing performance and drive improved marketing efficiency.
- Use Agile methodologies to manage and deliver a pipeline of planned improvements, utilising strong partner management skills to ensure the programme of delivery is successfully delivered and communicated.
- Deliver actionable recommendations to improve the effectiveness of marketing campaigns and initiatives. Influence key decision makers to ensure data driven insights are used to inform marketing planning and design.
- Act as a senior lead within the team, driving improvements in quality of work and ways of working.
- Expertise & experience in econometric and statistical modelling, including time-series analysis, panel data, survival analysis and causal inference methods.
- Proficiency in Python or R, with experience in statistical and machine learning libraries (Statsmodels, PyMC, causalml, survival etc)
- Experience working with large datasets, utilising strong skills in SQL and data wrangling, preferably in a marketing analytics function.
- Ability to translate complex statistical findings into clear, actionable insights for business decisions.
- Strong data visualisation, communication and partner management skills.
- Excellent problem-solving abilities and leadership skills to mentor junior team members and drive innovative solutions.
- MSc or PhD (or equivalent) in Econometrics, Statistics, Mathematics, Economics, Epidemiology, Public Health, or a related field with emphasis on applied statistics and data analysis.
- Bayesian Modelling (Hierarchical (Multilevel) models, Bayesian Shrinkage and Bayesian A/B testing).
- Marketing Mix Modelling (MMM) and media attribution models.
- Cloud computing platforms (AWS, GCP, Azure) and Git.
- Web and google analytics.
- Applying Machine Learning algorithms in causal inference setting, such as optimising IPTW weight estimation by minimising maximum covariant imbalance.
- Causal Machine Learning.
- Customer Focused - Self
- One Group, one team - Self
- Agile - Self
- Accountable - Self
- Amplify Capability - Self