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Growth Marketing Analyst (CO)
<h3 style="line-height:1.38;margin-top:21px;margin-bottom:5px;"><span style="font-size:17pt;font-variant:normal;white-space:pre-wrap;"><span style="font-family:Arial, sans-serif;"><span style="color:#000000;"><span style="font-weight:700;"><span style="font-style:normal;"><span style="text-decoration:none;">Growth Marketing Analyst (Full-Time, Remote)</span></span></span></span></span></span></h3><h3 style="line-height:1.656;text-align:justify;margin-top:19px;margin-bottom:16px;"><span style="font-size:13.999999999999998pt;font-variant:normal;white-space:pre-wrap;"><span style="font-family:Arial, sans-serif;"><span style="color:#000000;"><span style="font-weight:700;"><span style="font-style:normal;"><span style="text-decoration:underline;"><span><span>About the Company</span></span></span></span></span></span></span></span></h3><p style="line-height:1.38;text-align:justify;margin-top:16px;margin-bottom:16px;"><span style="font-size:11pt;font-variant:normal;white-space:pre-wrap;"><span style="font-family:Arial, sans-serif;"><span style="color:#000000;"><span style="font-weight:400;"><span style="font-style:normal;"><span style="text-decoration:none;">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.</span></span></span></span></span></span></p><p style="line-height:1.38;margin-bottom:5px;"><span style="font-size:13.999999999999998pt;font-variant:normal;white-space:pre-wrap;"><span style="font-family:Arial, sans-serif;"><span style="color:#000000;"><span style="font-weight:700;"><span style="font-style:normal;"><span style="text-decoration:underline;"><span><span>Position Overview</span></span></span></span></span></span></span></span></p><p style="line-height:1.38;margin-top:16px;margin-bottom:16px;"><span style="font-size:11pt;font-variant:normal;white-space:pre-wrap;"><span style="font-family:Arial, sans-serif;"><span style="color:#000000;"><span style="font-weight:400;"><span style="font-style:normal;"><span style="text-decoration:none;">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.</span></span></span></span></span></span></p><p style="line-height:1.38;margin-bottom:5px;"><span style="font-size:13.999999999999998pt;font-variant:normal;white-space:pre-wrap;"><span style="font-family:Arial, sans-serif;"><span style="color:#000000;"><span style="font-weight:700;"><span style="font-style:normal;"><span style="text-decoration:underline;"><span><span>Core Responsibilities</span></span></span></span></span></span></span></span></p><ul><li style="list-style-type:disc;"><span style="font-size:11pt;font-variant:normal;white-space:pre-wrap;"><span style="font-family:Arial, sans-serif;"><span style="color:#000000;"><span style="font-weight:400;"><span style="font-style:normal;"><span style="text-decoration:none;">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)</span></span></span></span></span></span></li><li style="list-style-type:disc;"><span style="font-size:11pt;font-variant:normal;white-space:pre-wrap;"><span style="font-family:Arial, sans-serif;"><span style="color:#000000;"><span style="font-weight:400;"><span style="font-style:normal;"><span style="text-decoration:none;">Surface data quality problems proactively. The current environment has known discrepancies across platforms that require investigation and resolution.</span></span></span></span></span></span></li><li style="list-style-type:disc;"><span style="font-size:11pt;font-variant:normal;white-space:pre-wrap;"><span style="font-family:Arial, sans-serif;"><span style="color:#000000;"><span style="font-weight:400;"><span style="font-style:normal;"><span style="text-decoration:none;">Build cohort level retention and LTV analysis from raw transactional data, segmented by acquisition channel, subscriber tier, and plan type</span></span></span></span></span></span></li><li style="list-style-type:disc;"><span style="font-size:11pt;font-variant:normal;white-space:pre-wrap;"><span style="font-family:Arial, sans-serif;"><span style="color:#000000;"><span style="font-weight:400;"><span style="font-style:normal;"><span style="text-decoration:none;">Develop and maintain a channel level payback model connecting acquisition costs to downstream subscription revenue, churn, and lifetime value</span></span></span></span></span></span></li><li style="list-style-type:disc;"><span style="font-size:11pt;font-variant:normal;white-space:pre-wrap;"><span style="font-family:Arial, sans-serif;"><span style="color:#000000;"><span style="font-weight:400;"><span style="font-style:normal;"><span style="text-decoration:none;">Support financial model updates by providing clean, segmented inputs (tier weighted COGS, gift vs paid subscriber separation, adjusted churn rates)</span></span></span></span></span></span></li><li style="list-style-type:disc;"><span style="font-size:11pt;font-variant:normal;white-space:pre-wrap;"><span style="font-family:Arial, sans-serif;"><span style="color:#000000;"><span style="font-weight:400;"><span style="font-style:normal;"><span style="text-decoration:none;">Validate and extend the existing Snowflake ETL pipeline from Recharge, backfill historical data where gaps exist, and work toward a single source of truth</span></span></span></span></span></span></li><li style="list-style-type:disc;"><span style="font-size:11pt;font-variant:normal;white-space:pre-wrap;"><span style="font-family:Arial, sans-serif;"><span style="color:#000000;"><span style="font-weight:400;"><span style="font-style:normal;"><span style="text-decoration:none;">Produce channel level performance reporting for recurring business reviews and leadership reporting packages.</span></span></span></span></span></span></li><li style="list-style-type:disc;"><span style="font-size:11pt;font-variant:normal;white-space:pre-wrap;"><span style="font-family:Arial, sans-serif;"><span style="color:#000000;"><span style="font-weight:400;"><span style="font-style:normal;"><span style="text-decoration:none;">Support A/B test design and statistical analysis for landing pages, email flows, and ad creative.</span></span></span></span></span></span></li></ul> <h3 style="line-height:1.656;text-align:justify;margin-top:19px;margin-bottom:16px;"><span style="font-size:13.999999999999998pt;font-variant:normal;white-space:pre-wrap;"><span style="font-family:Arial, sans-serif;"><span style="color:#000000;"><span style="font-weight:700;"><span style="font-style:normal;"><span style="text-decoration:underline;"><span><span>What Makes You the Right Fit</span></span></span></span></span></span></span></span></h3><ul><li style="list-style-type:disc;"><span style="font-size:11pt;font-variant:normal;white-space:pre-wrap;"><span style="font-family:Arial, sans-serif;"><span style="color:#000000;"><span style="font-weight:400;"><span style="font-style:normal;"><span style="text-decoration:none;">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.</span></span></span></span></span></span></li><li style="list-style-type:disc;"><span style="font-size:11pt;font-variant:normal;white-space:pre-wrap;"><span style="font-family:Arial, sans-serif;"><span style="color:#000000;"><span style="font-weight:400;"><span style="font-style:normal;"><span style="text-decoration:none;">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.</span></span></span></span></span></span></li><li style="list-style-type:disc;"><span style="font-size:11pt;font-variant:normal;white-space:pre-wrap;"><span style="font-family:Arial, sans-serif;"><span style="color:#000000;"><span style="font-weight:400;"><span style="font-style:normal;"><span style="text-decoration:none;">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.</span></span></span></span></span></span></li><li style="list-style-type:disc;"><span style="font-size:11pt;font-variant:normal;white-space:pre-wrap;"><span style="font-family:Arial, sans-serif;"><span style="color:#000000;"><span style="font-weight:400;"><span style="font-style:normal;"><span style="text-decoration:none;">You surface problems before being asked. If something looks off, you flag it—with context, a hypothesis, and ideally a fix.</span></span></span></span></span></span></li><li style="list-style-type:disc;"><span style="font-size:11pt;font-variant:normal;white-space:pre-wrap;"><span style="font-family:Arial, sans-serif;"><span style="color:#000000;"><span style="font-weight:400;"><span style="font-style:normal;"><span style="text-decoration:none;">You translate data into decisions. Your output isn't a spreadsheet; it's a clear narrative that non-technical stakeholders can act on.</span></span></span></span></span></span></li><li style="list-style-type:disc;"><span style="font-size:11pt;font-variant:normal;white-space:pre-wrap;"><span style="font-family:Arial, sans-serif;"><span style="color:#000000;"><span style="font-weight:400;"><span style="font-style:normal;"><span style="text-decoration:none;">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.</span></span></span></span></span></span></li></ul><p style="line-height:1.38;margin-bottom:5px;"><span style="font-size:13.999999999999998pt;font-variant:normal;white-space:pre-wrap;"><span style="font-family:Arial, sans-serif;"><span style="color:#000000;"><span style="font-weight:700;"><span style="font-style:normal;"><span style="text-decoration:underline;"><span><span>Required Skills</span></span></span></span></span></span></span></span></p><ul><li style="list-style-type:disc;"><span style="font-size:11pt;font-variant:normal;white-space:pre-wrap;"><span style="font-family:Arial, sans-serif;"><span style="color:#000000;"><span style="font-weight:400;"><span style="font-style:normal;"><span style="text-decoration:none;">SQL proficiency (writing queries against warehouse data, not just using a GUI)</span></span></span></span></span></span></li><li style="list-style-type:disc;"><span style="font-size:11pt;font-variant:normal;white-space:pre-wrap;"><span style="font-family:Arial, sans-serif;"><span style="color:#000000;"><span style="font-weight:400;"><span style="font-style:normal;"><span style="text-decoration:none;">Excel/Google Sheets at an advanced level (pivot tables, lookups, data modeling, large dataset manipulation)</span></span></span></span></span></span></li><li style="list-style-type:disc;"><span style="font-size:11pt;font-variant:normal;white-space:pre-wrap;"><span style="font-family:Arial, sans-serif;"><span style="color:#000000;"><span style="font-weight:400;"><span style="font-style:normal;"><span style="text-decoration:none;">Demonstrated comfort using AI/LLM tools (Claude, ChatGPT, Copilot, or similar) for data exploration, code generation, and analytical workflows</span></span></span></span></span></span></li><li style="list-style-type:disc;"><span style="font-size:11pt;font-variant:normal;white-space:pre-wrap;"><span style="font-family:Arial, sans-serif;"><span style="color:#000000;"><span style="font-weight:400;"><span style="font-style:normal;"><span style="text-decoration:none;">Demonstrated ability to reconcile conflicting data sources and determine which source to trust</span></span></span></span></span></span></li><li style="list-style-type:disc;"><span style="font-size:11pt;font-variant:normal;white-space:pre-wrap;"><span style="font-family:Arial, sans-serif;"><span style="color:#000000;"><span style="font-weight:400;"><span style="font-style:normal;"><span style="text-decoration:none;">Experience building cohort retention curves and LTV models from raw transactional data</span></span></span></span></span></span></li><li style="list-style-type:disc;"><span style="font-size:11pt;font-variant:normal;white-space:pre-wrap;"><span style="font-family:Arial, sans-serif;"><span style="color:#000000;"><span style="font-weight:400;"><span style="font-style:normal;"><span style="text-decoration:none;">Experience working with ecommerce or subscription data (Shopify, Recharge, Stripe, or equivalents)</span></span></span></span></span></span></li><li style="list-style-type:disc;"><span style="font-size:11pt;font-variant:normal;white-space:pre-wrap;"><span style="font-family:Arial, sans-serif;"><span style="color:#000000;"><span style="font-weight:400;"><span style="font-style:normal;"><span style="text-decoration:none;">Comfortable working with messy, incomplete, or conflicting data where clean join keys do not exist</span></span></span></span></span></span></li><li style="list-style-type:disc;"><span style="font-size:11pt;font-variant:normal;white-space:pre-wrap;"><span style="font-family:Arial, sans-serif;"><span style="color:#000000;"><span style="font-weight:400;"><span style="font-style:normal;"><span style="text-decoration:none;">Self directed problem solver who surfaces issues before being asked. This is not a ticket driven reporting role.</span></span></span></span></span></span></li><li style="list-style-type:disc;"><span style="font-size:11pt;font-variant:normal;white-space:pre-wrap;"><span style="font-family:Arial, sans-serif;"><span style="color:#000000;"><span style="font-weight:400;"><span style="font-style:normal;"><span style="text-decoration:none;">Strong written communication in English for presenting findings to non technical stakeholders</span></span></span></span></span></span></li></ul><p style="line-height:1.38;margin-bottom:5px;"><span style="font-size:13.999999999999998pt;font-variant:normal;white-space:pre-wrap;"><span style="font-family:Arial, sans-serif;"><span style="color:#000000;"><span style="font-weight:700;"><span style="font-style:normal;"><span style="text-decoration:underline;"><span><span>Preferred Skills</span></span></span></span></span></span></span></span></p><ul><li style="list-style-type:disc;"><span style="font-size:11pt;font-variant:normal;white-space:pre-wrap;"><span style="font-family:Arial, sans-serif;"><span style="color:#000000;"><span style="font-weight:400;"><span style="font-style:normal;"><span style="text-decoration:none;">Experience with Snowflake or similar data warehouses, including pipeline validation and data engineering</span></span></span></span></span></span></li><li style="list-style-type:disc;"><span style="font-size:11pt;font-variant:normal;white-space:pre-wrap;"><span style="font-family:Arial, sans-serif;"><span style="color:#000000;"><span style="font-weight:400;"><span style="font-style:normal;"><span style="text-decoration:none;">Experience with ad platform data (Meta Ads Manager, Google Ads) and understanding of attribution models</span></span></span></span></span></span></li><li style="list-style-type:disc;"><span style="font-size:11pt;font-variant:normal;white-space:pre-wrap;"><span style="font-family:Arial, sans-serif;"><span style="color:#000000;"><span style="font-weight:400;"><span style="font-style:normal;"><span style="text-decoration:none;">Experience with Klaviyo or similar email/SMS marketing platforms</span></span></span></span></span></span></li><li style="list-style-type:disc;"><span style="font-size:11pt;font-variant:normal;white-space:pre-wrap;"><span style="font-family:Arial, sans-serif;"><span style="color:#000000;"><span style="font-weight:400;"><span style="font-style:normal;"><span style="text-decoration:none;">Experience building AI-assisted analytical workflows (e.g., using LLMs for data reconciliation, anomaly detection, or automated reporting)</span></span></span></span></span></span></li><li style="list-style-type:disc;"><span style="font-size:11pt;font-variant:normal;white-space:pre-wrap;"><span style="font-family:Arial, sans-serif;"><span style="color:#000000;"><span style="font-weight:400;"><span style="font-style:normal;"><span style="text-decoration:none;">Experience with Source Medium or similar analytics reporting tools</span></span></span></span></span></span></li><li style="list-style-type:disc;"><span style="font-size:11pt;font-variant:normal;white-space:pre-wrap;"><span style="font-family:Arial, sans-serif;"><span style="color:#000000;"><span style="font-weight:400;"><span style="font-style:normal;"><span style="text-decoration:none;">Python or R for data manipulation and automation</span></span></span></span></span></span></li><li style="list-style-type:disc;"><span style="font-size:11pt;font-variant:normal;white-space:pre-wrap;"><span style="font-family:Arial, sans-serif;"><span style="color:#000000;"><span style="font-weight:400;"><span style="font-style:normal;"><span style="text-decoration:none;">Financial modeling experience (LTV, payback period, contribution margin)</span></span></span></span></span></span></li><li style="list-style-type:disc;"><span style="font-size:11pt;font-variant:normal;white-space:pre-wrap;"><span style="font-family:Arial, sans-serif;"><span style="color:#000000;"><span style="font-weight:400;"><span style="font-style:normal;"><span style="text-decoration:none;">Experience in a subscription box or D2C subscription business</span></span></span></span></span></span></li></ul>