You will partner with product, design, and engineering teams to obtain insights, design experiments, and guide important product decisions.
You will support strategic plans with data insights, performing deep-dives into user behaviour, segmented views and product efficacy.
You will provide tailored analysis for specific products and strategies, define critical business and product metrics, and make regular recommendations for continuous improvements.
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Partner with product, design, and engineering teams to obtain insights, design experiments, and lead important product decisions.
Support strategic plans with data insights, performing deep-dives into user behavior, segmented views and product efficacy.
Provide tailored analysis for specific products and strategies, define critical business and product metrics, and make regular recommendations for continuous improvements.
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Partner with marketing leaders and stakeholders to understand business objectives, marketing channels, data sources, measurement constraints, and strategic priorities.
Translate marketing needs into relevant measurement science solutions, evaluating multiple methodological approaches and communicating trade-offs between attribution models, incrementality testing, and causal inference methods.
Design and implement advanced attribution methodologies (multi-touch, algorithmic, and rule-based models) to accurately measure campaign contribution across paid channels and customer touchpoints.
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Define and own the analytics roadmap, aligning it with MR DIY's business objectives and the broader digital transformation strategy.
Identify high-value analytics opportunities across merchandising, supply chain, store operations, finance, and customer/loyalty domains, and prioritise based on business impact.
Translate ambiguous business questions into structured analytics problems with clear success measures.
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Transform data into reusable analytics assets - datasets, reports, pipelines and notebooks in the curated layer of the Lakehouse and Data Warehouse in Microsoft Fabric.
Conduct deep-dive analytics based on business priorities and identify improvement opportunities.
Build data pipelines and manage data migration projects.
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Acts as a focal point for communicating related system issues within the department and collaborates with other business teams and vendors on new initiative, changes, fixes, and updates.
Works closely with business units (Eg: Sales, Commercial, Finance, Procurement, Production, others support function) in identifying, evaluating, selecting, and implementing specific business technologies that support the business plans and IT strategies.
Design, prepare strategies, develop and implement the data solution, roadmap, infrastructure of Mamee.
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Define and own the analytics roadmap, aligning it with MR DIY's business objectives and the broader digital transformation strategy.
Identify high-value analytics opportunities across merchandising, supply chain, store operations, finance, and customer/loyalty domains, and prioritise based on business impact.
Translate ambiguous business questions into structured analytics problems with clear success measures.
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To lecture/teach the course(s) assigned and cover the syllabi outlined for the assigned course(s) in a logical and readily understood sequence, and in accordance with students' assignment requirements.
To assist students in the understanding of the topics covered and generally to prepare them for their final examinations.
To guide students in the understanding of assignment requirements.
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Analyse complex retail inventory, replenishment and allocation problems involving stores, SKUs, stock, sales, warehouse supply, lead time, festivals and other business conditions.
Take ownership of analysis from problem understanding, data identification and validation through analysis, findings, recommendations and follow-up.
Use SQL, Python/pandas, Excel and BI tools to process, analyse and visualise large datasets.
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Deliver customized reports and supporting dashboard that enabled consistent data tracking and create visibility to multifunctional teams. Examples of data to work with are distributor sales data, scanned sales from customers, IQVIA and Nielsen
Managing distributor portal (ZIP online, EZRX) to map customers to sales representative.
Managing internal application (Snowflake) to map internal product code to distributor product code
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Analyse complex retail inventory, replenishment and allocation problems involving stores, SKUs, stock, sales, warehouse supply, lead time, festivals and other business conditions.
Take ownership of analysis from problem understanding, data identification and validation through analysis, findings, recommendations and follow-up.
Use SQL, Python/pandas, Excel and BI tools to process, analyse and visualise large datasets.
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