Data Scientist

• Build data-powered solutions forming part of our product
• Define and execute data science experiments
• Create PoC and move them to production with support from ML and Data Engineers
• Conduct exploratory data analysis
• Perform feature engineering
• Engage in time series forecasting
• Develop, deploy, and monitor models
• Conduct A/B testing
• Communicate findings and mine data for insights
• Influence organisational strategies based on insights

Data Scientist – Junior/Mid

• Own the full lifecycle of complex modelling programmes across Customer & Commercial Intelligence: CLTV, Churn Prediction, Propensity to Buy, and Next Most Likely Product (NMLP)
• Architect multi-horizon churn models and build the churn intervention scoring layer that prioritises at-risk merchants for Account Management teams
• Lead the NMLP engine — designing and productionizing a multi-output recommendation system that identifies the next product across myPOS's full catalogue
• Take technical ownership of core fraud model components: transaction-level classifiers, merchant behaviour anomaly detectors, and new-account fraud scorers optimised for high-throughput, low-latency inference
• Architect and own the Next Best Action (NBA) decisioning engine - a real-time system that selects the highest-expected-value action for each merchant at every interaction
• Design and build production-grade agentic AI systems that automate high-value analytical and operational workflows
• Define and execute experiment designs for online evaluation - A/B tests, uplift experiments, and bandits - and analyse results with statistical rigour
• Set and enforce technical standards across the team: code quality, reproducibility, evaluation rigour, model documentation, and MLOps practices
• Produce high-quality model documentation and present complex modelling work clearly to stakeholders across Sales, Marketing, Risk, Product, and Operations

Senior Data Scientist

• Lead and build a new analytics team that drives product growth through data-driven insights and AI-powered analysis.
• Define and execute the analytics roadmap, guiding proactive analyses to uncover growth opportunities.
• Build and mentor a high-performing team of analysts, establishing excellence in SQL, visualization, and statistical methods.
• Champion AI integration to optimize analytical workflows and unlock deeper product insights.
• Partner closely with Product Managers as their primary data ally, translating complex findings into clear, actionable recommendations.
• Collaborate with data engineers and implementation specialists to prioritize tracking, define schemas, and guide data modeling.
• Enable broader analytics teams through training on behavioral data usage, querying best practices, and dataset documentation.

Product Analytics Team Lead

• Manage each of the data management projects to which assigned; provide leadership to the corresponding data management teams.
• Represent WCT in all dealings with Sponsors with respect to the Data Management aspects of the projects to which assigned.
• Liaise with the Director, Data Management at regular intervals to discuss progress and any issues outstanding.
• Take responsibility for staff training for all projects to which assigned; both direct involvement in training and supervision of staff assigned to training.
• Ensure that all data management operations are conducted to WCT SOPs; contribute to the ongoing revision/improvement of these SOPs.
• Create and review project specific documentation for assigned trials, i.e. the Data Management Plan and the Data Management File.
• To ensure that adequate QC checks (including spot checks) and Database Quality Assessments on the clinical databases of assigned projects.

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