Senior Data Analyst

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.

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.

As our Senior Data Analyst, you will be responsible for:

• 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.

• 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.

• 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.

• 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…