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Data Ecosystem
- Performs data reconciliation / manipulation tasks to proactively optimize data architecture
- Monitors data hygiene inputs and outputs by continuously safeguarding data quality, integrity, privacy and usability
- Consolidates data gathered across multiple sources along the customer journey (structured + unstructured) to identify macro-level themes
- Identifies opportunities for automation
Marketing / CRM Analytics
- Defines and quantifies current customer base
- Implements strategies to maximize customer retention, lifetime value and share of wallet
- Partners with technical advisors on predictive analysis, audience segmentation, attribution modeling and hyper-personalization frameworks
- Analyzes campaign performance and defines logic for campaign automation
- Develops an in-depth understanding of the customer journey and churn behaviors
- Designs A/B and longitudinal test plans taking into account control groups, statistical significance, audience size, incrementality, etc.
Product Analytics
- Provides perspective and guidance to product teams to ultimately inform buying investments, prioritization backlogs, new product development and iterations on existing products
- Gathers requirements and translate business problems into structured quantitative analyses
- Produces recurrent operational reports and dashboards that highlight main product opportunities on an ongoing basis (e.g., product satisfaction, returns, reviews, etc.)
- Partners with Insights team, to fill informational gaps with ad hoc research when necessary (e.g., archetypes, qualitative deep-dive, category U&A, volumetric study, etc.)
Reporting & Visualization
- Transforms data into inspiring visualizations that accelerate continued innovation and growth
- Socializes results in a clear, concise and compelling way that inspires action
- Drives data literacy across the business by democratizing access to timely and accurate information and empowering cross-functional users to make data-driven decisions on an ongoing basis
The ideal candidate is an analytically-inclined, dynamic self-starter, skilled in all aspects of data analytics, including mining, generation, interpretation and visualization with a keen propensity to finding patterns and root causes in large datasets.
Skills & Experience
- Exceptional analytical skills: ability to navigate large amounts of data and provide critical thinking towards actionable analytics
- Comfortable using SQL or other programming languages to query large enterprise data warehouses from scratch (experience with BigQuery an asset
- Experience developing, maintaining and managing dashboards and scorecards on visualization tools.(You will need to set everything up from ground up)
- Strong expertise with analytical and statistical methods across channels (online, offline, wholesale)
- Knowledge of main retail performance indicators (experience with Mobile Aplications)
- Strong business acumen
- Demonstrated commitment to the accuracy and completeness of the information
- Excellent communication skills, in English
