Data Analyst; Commerce Intelligence

Location:

NYC, remote available for exceptional, US-based candidates

Reports To:

Chief Marketing Officer (CMO)

Daash Intelligence is a well‑funded tech start‑up at the forefront of next‑gen predictive commerce intelligence. Our mission is to make retail markets more transparent, enabling customers to track and predict market trends more easily, thoroughly, and affordably. This is crucial because countless small and mid‑size consumer brands struggle to compete with larger companies that invest millions in market research. Daash tackles this by democratizing access to the actionable intelligence these brands need to thrive.

Our rapidly growing team of dedicated engineers, scientists, and business leaders is united in this vision, and the market response has been incredible. Our clients are high‑profile brands and manufacturers, who are using our platform for critical business decisions. Join us and help shape the future of commerce intelligence.

We are seeking a highly analytical and insight‑driven Data Analyst to join our growing team. This role sits at the intersection of data analysis, client engagement, and strategic storytelling. Reporting to the CMO, you will work closely with marketing, client services, product, and directly with client teams to translate complex datasets into clear, compelling insights that inform real‑world strategic decisions for beauty, personal care, and health & wellness brands.

This role requires comfort operating in a project‑based, client‑facing environment—owning discrete analytical work streams, collaborating directly with brand partners, and delivering high‑quality insights on defined timelines. Success in this role means not only producing strong analysis, but also building trust with clients through clear communication, responsiveness, and thoughtful interpretation of data.

• Client‑Facing Analytics:
  Partner directly with client teams on defined analytical projects, including category deep dives, competitive benchmarking, performance diagnostics, and ad hoc strategic analyses.
• Project Ownership:
  Manage analysis work streams end‑to‑end, from scoping and data exploration through insight development and presentation.
• Insight Generation:
  Analyze large, multi‑dimensional datasets related to retail sales, competitive performance, distribution, velocity, and category trends to surface actionable insights.
• Data Storytelling:
  Create clear, visually compelling charts, dashboards, and presentations that translate data into strategic narratives for client and executive audiences.
• Marketing & Thought Leadership Support:
  Collaborate with the marketing team to develop data‑backed reports, POVs, and external‑facing content that reinforces Daash's differentiated weekly intelligence.
• Cross‑Functional
  
  Collaboration:
  
  Work closely with product, data, and client services teams to ensure analyses are accurate, scalable, and aligned with platform capabilities.
• Data Judgment & Interpretation:
  Apply sound judgment in interpreting trends, anomalies, and limitations in the data, clearly communicating confidence levels and assumptions.

• 2+ years of experience as a Data Analyst, Analytics Associate, or similar role
• Experience working with consumer brands or data/platform vendors serving beauty, personal care, or health & wellness brands
• Most desirable experience includes working as an analyst for a consumer brand, retailer, or in service of the retail industry (e.g., retail analytics, or market research)
• Alternative but relevant experience may include analytical roles in financial markets or investment‑oriented environments
• Prior experience supporting client‑facing, project‑based analytical work is strongly preferred

• Expertise in Excel
• Comfort working with large, structured datasets across multiple dimensions (retailer, channel, region, time)
• Strong proficiency with BI and visualization tools (e.g., Tableau, Power BI, Looker, or similar)
• SQL proficiency is a plus, but not required

• Ability to interpret data and generate insights, not just outputs
• Strong visual and chart‑based storytelling…