Senior Data Analyst (Marketing)

About our Company

We are a global team operating a health and wellness brand serving over 2 million customers worldwide. We have a team of ~40 full-time employees globally, headquartered in Singapore. Our brand generates more than $100M per year in revenue and operates profitably with close to 100,000 monthly subscribers. We continuously strive to bring the best functional products to improve women's health, with a focus on making our products clinically-influenced yet approachable to everyday consumers.

Overview of the Role

As we’re building the infrastructure to enable and support the next leg of growth ($500M to $1B), we’re looking for a Senior Data Analyst to lead efforts in managing and analyzing marketing, financial, and operations data to enable and support business growth opportunities. You will report to the Head of Growth and work across functional areas to translate complex and sometimes unstructured datasets into actionable insights to identify new growth opportunities or optimize efforts in existing projects. This role focuses on growing or optimizing the following metrics:

• Average order value (AOV)
• Conversion rate (CVR)
• Lifetime value (LTV), which includes interim values like 3, 6, and 12 months
• Payback periods
• Subscription churn and recovery
• …and other growth metrics, if any

The core responsibilities for this role include:

• Developing forward-looking data analysis capabilities for a women’s health brand with long-term growth ambitions
• Building and managing a team of data analyst(s) and data assistant

Part 1: Develop Right-Sized Data Analysis Infrastructure

• Audit data analytics needs for the organization with growth and marketing needs in mind
• Recommend and implement right-sized data management solutions (including but not limited to data warehouse, visualization, programming language, etc.) to meet present and mid-term needs (e.g. BigQuery, Fivetran, Tableau, PowerBI)
• Establish and refine data models within the database to ensure efficient data storage and retrieval.
• Create and optimize SQL queries, views, and stored procedures. 
• Contribute to solutions for real-time data retrieval from various sources, including API integrations and new platform solutions selection.

Part 2: Enable Marketing Insights

• Marketing is our growth engine, so enabling marketing-related insights is a core priority for the data team before all else.
• Increase access to internal data sources including but not limited to post-purchase KnoCommerce surveys, customer surveys, clinical trial results, business performance data across Shopify, Amazon.com, Walmart.com, Meta, Google, Helium10, Hyros, etc. using data management and visualization tools
• Increase access to external and relevant data sources including but not limited to macro data sources like Amazon.com, iHerb, industry research studies, CPI, DTCCI, etc. and micro data sources like Meta Ads library, Google Ads transparency center, ad spy tools like Atria and Foreplay, etc.
• Using experienced knowledge of acquisition and retention marketing KPIs, synthesize data across multiple sources to develop insights and to tell a story with data. 
• Develop actionable optimization recommendations.
• Use advanced segmentation methodologies to group customers by cohort, lifetime value, products purchased, etc. Build models to predict lifetime value and score customers on dimensions such as likelihood to buy.
• Analyze Customer Retention and Behavior. Examples:
• Analyze Subscription Retention Rates: Assess retention rates and compare group performance.
• Perform Cohort Analysis: Conduct analysis to understand customer behavior on first and second purchases, and channel-based behavior.
• Incrementality Tests for Campaigns: Video lifts and whitelisted campaigns on customer behavior.
• Analyze Brand and Promotions Impact. Examples:
• Measure and Monitor Brand Changes: Track and analyze the impact of brand changes.
• Analyze Impact of Free Shipping Offers: Assess the impact of offering free shipping to specific regions.
• Conduct Promotional Analysis: Evaluate the effectiveness of various promotions and marketing campaigns.

What working with us looks like

First few weeks

• Company onboarding: Our team member will introduce you to the company and share more about our business and background with you 
• Team onboarding: Our team member(s) will introduce you to the marketing team and operations, and guide you through your responsibilities. You will likely take 2-3 weeks to familiarize yourself with your routine and tasks. A buddy will be assigned to you so you can reach out anytime you need help
• Career review:
• Informal: After 4-6 weeks
• Formal, 1st: After 3 months
• Formal, 2nd: After 6 months

Preferred Qualifications

• Bachelor's degree in Computer Science, Statistics, Mathematics, Marketing, or another research-related field.
• 5+ years of experience as a Data Analyst or similar role, demonstrating expertise in AI-driven analytics and marketing insights.
• Strong understanding of marketing concepts, particularly AOV, LTV, conversion rates, and customer acquisition costs, coupled with expertise in leveraging AI for marketing intelligence.
• Excellent communication and presentation skills, especially in conveying insights to non-technical stakeholders.
• Experience with Git and code management practices.
• Proven ability to work independently in a fast-paced environment
• Experience leading or managing teams preferred

Soft skills

• Meticulous: Pays close attention to details
• Process-oriented: Thinks through potential scenarios in detail to verify and confirm the right setup
• Numbers-driven: Familiarity and comfort working with numbers
• Love for Problem-solving: Has a positive attitude when problems surface, and focuses on finding a solution
• Intellectual curiosity: Openness and curiosity in learning new things, including knowledge and tools

Technical skills

• CRM: Shopify, Hubspot, Salesforce, or something similar
• Marketing API: Familiarity with Supermetrics or something similar
• Marketing attribution tools: Familiarity with Google Analytics 4, Hyros, TripleWhale, Northbeam, or something similar
• Data visualization tool: Familiarity with Tableau, Google Data Studio, PowerBI, or something similar
• Data science language: Familiarity with Python, R or something similar

Work Arrangements

• For Singapore-based team members, working hours are fixed, from 10am to 7pm SGT from Mon - Fri
• For remote team members, your working hours will be discussed prior to employment
• Lunch is one hour and flexible (you can decide what time to take your one hour off)
• Once-a-week team meetings (time TBD), with shorter check-in calls throughout the week when necessary

• Competitive salary and performance-based bonuses.
• Opportunities for professional development and advancement.
• Collaborative and dynamic work environment.