Senior Data Analyst

Atomic•Miami, FL

About The Position

About Us Atomic is a venture studio that builds companies from scratch. We’re a team of seasoned entrepreneurs and operators who have built and scaled some of the most successful startups in the world. We specialize in creating disruptive businesses that solve real problems for e-commerce brands. The Opportunity We are looking for our first Senior Data Analyst to be a foundational member of our growing Data team, with a primary focus on preparing the company for our major Q1 2026 launch. This is a highly visible, cross-functional role, reporting directly to the Co-Founder & CPO. You will be the primary analytical partner for our Leadership, Growth, Product, Operations, and R&D teams, laying the groundwork for how we measure, analyze, and optimize performance from Day 1 (launch in Q1 2026). If you thrive on solving challenging business problems within a fast-paced e-commerce environment, enjoy diving deep into diverse datasets, and can effectively communicate findings to technical and non-technical audiences, this high-impact role is for you.

Requirements

Domain Experience: 4+ years of professional experience as a Data Analyst, with significant and demonstrable experience working within an e-commerce or Direct-to-Consumer (DTC) business. Including significant experience presenting findings to senior leaders or executive teams.
Launch Experience: Demonstrated experience preparing analytical infrastructure and metrics for a major product or company launch.
Growth Marketing Analytics: Proven ability to analyze common DTC/Growth metrics (LTV, CAC, ROAS, payback period, attribution) and interpret performance marketing data from platforms like Google Ads, Meta, etc.
SQL Mastery: Expert proficiency in writing complex, efficient SQL queries for data extraction and manipulation. Experience with AI reporting tools.
Statistical Analysis: Strong foundation in statistical methods (e.g., regression, hypothesis testing, A/B testing methodology) and experience applying them to business problems.
Data Visualization: Advanced experience with at least one major BI tool (e.g., Looker, Tableau, Power BI, Metabase) for dashboard creation and data storytelling.
Communication: Exceptional written and verbal communication skills, with the ability to translate technical findings into clear, actionable business recommendations for executive audiences.

Nice To Haves

Experience with a modern data warehouse (e.g., Snowflake, BigQuery, Redshift).
Prior experience in a high-growth startup environment or being the first dedicated analyst for a function.
Familiarity with data modeling, ETL/ELT concepts, and data governance principles.
Experience with AI reporting tools and methods

Responsibilities

Launch Readiness & Strategy Metric Definition: Work directly with Leadership to define, standardize, and implement the core business KPIs and metrics that will measure the success of the Q1 2026 launch across all departments.
Data Structure: Partner with engineering to ensure all tracking (web, marketing, operations) is implemented and structured to enable clean, reliable analysis immediately post-launch.
Model Building: Develop foundational analytical models (e.g., LTV and CAC forecasting) to project launch performance and set initial performance targets.
Core Analysis & Reporting Cross-Functional Partnership: Act as the dedicated analytical liaison for our Leadership, Growth, Product, Operations, and R&D departments.
Deep Dive Analysis: Conduct complex, end-to-end analyses to identify trends, opportunities, and root causes of performance changes across key DTC metrics (e.g., LTV, CAC, AOV, conversion rates, repurchase rates, operational efficiency, and research outcomes).
Dashboard Development: Design, build, and maintain robust reports and self-service dashboards (using tools like [Looker/Tableau/Power BI]) that will be utilized by all teams immediately following the launch.
Strategic Collaboration Leadership/Executive: Develop and present high-level, strategic analyses on company performance, market opportunities, and potential risks to the executive team and stakeholders.
Model business impact for key investment decisions and strategic initiatives.
Growth: Deeply analyze pre-launch marketing effectiveness, guide audience segmentation, and build the initial reporting framework necessary to optimize spend across channels and maximize LTV immediately following the Q1 launch.
Product: Support product development by setting up event tracking and defining key product usage funnels to measure launch engagement and feature adoption.
Operations: Define and measure operational processes (e.g., supply chain, fulfillment logistics, and inventory management) to ensure scalability post-launch.
R&D: Partner with R&D teams to structure, analyze, and report on experimental data, helping to validate hypotheses and accelerate innovation.