Lifecycle Marketing Senior Data Analyst

Responsibilities 

Data Strategy and Measurement plan (for Regional teams) 

• Data foundations - Strategize and design measurement framework, for each lifestage in our scope and set data-direction for Lifecycle Marketers in APJ & EMEA. 

• Measurement plan – Own, track and manage the data goals and KPIs, in partnership with Lifecycle Marketers, across all the post-purchase lifestages of different customer personas. 

• Experience monitoring - Partner with Lifecycle Marketers in APJ & EMEA, to track and monitor the campaign and test performances. 

• Data modelling and reporting - Develop and own sophisticated data models, reports and dashboards, to track our initiatives, and derive actionable insights. 

Data Analysis and Insights 

• Data analysis - Analyse complex data sets to identify trends, patterns, and insights, for initiatives within the Lifecycle Marketing team. 

• Experience optimization - Review performances of existing customer journeys and uncover gaps and opportunities for optimization. 

• Strategic recommendations - Review customer behaviour and identify gaps and opportunities to accelerate time to value, improve adoption rates, and long-term customer satisfaction. 

Collaboration & Communications 

• Data governance - Own and co-create, with other data analysts, data governance for the team and quality initiatives. 

• Global data support - Provide analytical support to global Lifecycle Marketers, on need basis, through data analysis and insights, with other data analysts. 

• Technical and operational collaboration - Collaborate with marketing and technical global teams, for converting insights into actionable data triggers. 

• Communications - Own and drive ‘data and insights’ specific communications and presentations to senior stakeholders and internal teams. 

 
Expected qualifications 

• Overall 10 years of exp. with minimum 5+ years in complex data analysis and strategic insights, from B2B, SaaS background. 

• Experience working in Marketing / Sales / Customer behaviour or product usage related area is preferred. 

• Proficiency in SQL, data visualization tools (e.g., Looker, Tableau, Power BI) to extract and present insights, is a must.  

• Familiarity with Python or R, advanced statistical analysis techniques and machine learning algorithms, data modelling, data warehousing, and ETL processes is preferred. 

• Demonstrated experience working with APJ, EMEA and global stakeholders - Marketing managers and operations specialists, data experts, product owners, and sometimes Engineers. 

• Strong communication skills with the ability to translate complex data into clear, concise and compelling manner to a variety of stakeholder.