We’re CatchCo, makers of Mystery Tackle Box — the original fishing subscription box since 2012. Our mission is to Rescue Humanity From the Indoors. Today, we help millions get outside with products sold at Walmart, Dick’s Sporting Goods, Amazon, and our website. We’ve moved past the venture-backed hype and are now under new ownership, building a lean, profitable, and lasting business. If you believe in getting people outdoors and doing work that matters, you’ll fit right in.
Position Overview
Investigate, reconcile, and build the data infrastructure for a subscription ecommerce company (Mystery Tackle Box / Catch Co) that is rebuilding its growth marketing function from scratch. The data environment spans multiple platforms with known quality issues, conflicting sources, and no unified reporting layer. This role is equal parts detective work and system building.
Core Responsibilities
- Investigate and reconcile data across Recharge (subscription management), Shopify (ecommerce), Klaviyo (email/SMS), Source Medium (analytics reporting), Snowflake (warehouse), and paid ad platforms (Meta, Google)
- Surface data quality problems proactively. The current environment has known discrepancies across platforms that require investigation and resolution.
- Build cohort level retention and LTV analysis from raw transactional data, segmented by acquisition channel, subscriber tier, and plan type
- Develop and maintain a channel level payback model connecting acquisition costs to downstream subscription revenue, churn, and lifetime value
- Support financial model updates by providing clean, segmented inputs (tier weighted COGS, gift vs paid subscriber separation, adjusted churn rates)
- Validate and extend the existing Snowflake ETL pipeline from Recharge, backfill historical data where gaps exist, and work toward a single source of truth
- Produce channel level performance reporting for recurring business reviews and leadership reporting packages.
- Support A/B test design and statistical analysis for landing pages, email flows, and ad creative.
- You're a data detective, not a dashboard reader. When numbers don't add up across platforms, you dig until you find out why—and you document what you found so it doesn't happen again.
- You're comfortable with ambiguity. Messy data, missing join keys, and conflicting sources don't stop you—they're the job, and you know how to work through them systematically.
- You build for permanence. You don't just answer the question in front of you; you build the model, pipeline, or framework that answers the next ten questions too.
- You surface problems before being asked. If something looks off, you flag it—with context, a hypothesis, and ideally a fix.
- You translate data into decisions. Your output isn't a spreadsheet; it's a clear narrative that non-technical stakeholders can act on.
- You use AI tools as a force multiplier. You reach for LLMs, code interpreters, and AI assisted analysis when they can accelerate your work. Not as a crutch, but as a way to move faster through data cleaning, hypothesis generation, and exploratory analysis.
Required Skills
- SQL proficiency (writing queries against warehouse data, not just using a GUI)
- Excel/Google Sheets at an advanced level (pivot tables, lookups, data modeling, large dataset manipulation)
- Demonstrated comfort using AI/LLM tools (Claude, ChatGPT, Copilot, or similar) for data exploration, code generation, and analytical workflows
- Demonstrated ability to reconcile conflicting data sources and determine which source to trust
- Experience building cohort retention curves and LTV models from raw transactional data
- Experience working with ecommerce or subscription data (Shopify, Recharge, Stripe, or equivalents)
- Comfortable working with messy, incomplete, or conflicting data where clean join keys do not exist
- Self directed problem solver who surfaces issues before being asked. This is not a ticket driven reporting role.
- Strong written communication in English for presenting findings to non technical stakeholders
Preferred Skills
- Experience with Snowflake or similar data warehouses, including pipeline validation and data engineering
- Experience with ad platform data (Meta Ads Manager, Google Ads) and understanding of attribution models
- Experience with Klaviyo or similar email/SMS marketing platforms
- Experience building AI-assisted analytical workflows (e.g., using LLMs for data reconciliation, anomaly detection, or automated reporting)
- Experience with Source Medium or similar analytics reporting tools
- Python or R for data manipulation and automation
- Financial modeling experience (LTV, payback period, contribution margin)
- Experience in a subscription box or D2C subscription business
Skills Required
- SQL proficiency (writing queries against warehouse data)
- Advanced Excel/Google Sheets (pivot tables, lookups, large dataset manipulation)
- Comfort using AI/LLM tools (Claude, ChatGPT, Copilot) for data exploration and code generation
- Ability to reconcile conflicting data sources and determine trusted sources
- Experience building cohort retention curves and LTV models from raw transactional data
- Experience working with ecommerce or subscription data (Shopify, Recharge, Stripe or equivalents)
- Comfort working with messy, incomplete, or conflicting data without clean join keys
- Self-directed problem solver who proactively surfaces issues
- Strong written communication in English for presenting findings to non-technical stakeholders
- Experience with Snowflake or similar data warehouses, including pipeline validation
- Experience with ad platform data and attribution (Meta Ads Manager, Google Ads)
- Experience with Klaviyo or similar email/SMS marketing platforms
- Experience building AI-assisted analytical workflows (LLMs for reconciliation, anomaly detection, reporting)
- Experience with Source Medium or similar analytics reporting tools
- Python or R for data manipulation and automation
- Financial modeling experience (LTV, payback period, contribution margin)
- Experience in a subscription box or D2C subscription business
What We Do
At Catch Co, our purpose is to rescue people from the indoors by connecting them with America’s top outdoor sport: fishing. More than 50 million Americans fish every year and Catch Co is the industry leader in creating products, content, and experiences that modern anglers love. Most importantly, we aim to have the most loyal customers in the outdoors industry. We are building 3 unique businesses to deliver on that mission: - Mystery Tackle Box - Founded in 2012, MTB is the most popular fishing subscription service in the world, with over 5 million boxes shipped (and counting!). - Karl’s Bait and Tackle - Launched in 2018, Karl’s is a unique and exciting ecommerce experience that brings the local tackle shop to the Internet. - Catch Co. fishing products - Catch Co also designs and develops some of fishing’s most popular and innovative brands and products, sold online and in retail throughout the world. To support these businesses, we have built a best-in-class foundation of creativity, technology, data, and a fun and supportive culture. We have also built durable partnerships with some of the industry’s most impactful content creators, influencers, product designers, and more. As we execute against our mission, our team members remain curious, action-oriented, and collaborative. If that sounds like you, we would love to meet you. These are our core values: Passion: We love what we do and we take pride in our work. Action: We work hard to get stuff done, with urgency. Optimism: We believe that we will succeed, and we are willing to keep trying new things. Honesty: We tell it like it is, communicate issues, take accountability and use data to make decisions. We are transparent with customers, partners and employees. Curiosity: We look for ways to make things better. We focus on solutions, not problems. #happydance: We create happiness for our customers and for each other. Everybody can fish with us!
Why Work With Us
Our culture is fast-moving, hardworking, welcoming and friendly, and we keep our calendar full of opportunities to learn from coworkers and foster community. We love a good team event (like trivia or Quiplash), continued learning (fireside chats led by colleagues), and niche Slack channels like #mlb, #bachelor, #unpopular_opinions, and #badjokes
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