Analytics Lead

Flagship is building an innovative Sales and Operations Planning (S&OP) software that empowers DTC retail brands to maximize growth efficiency. Our platform seamlessly integrates with their first-party data to provide tailored insights based on advanced data analytics to drive cross-functional strategic decision-making.

At Flagship, we have built a multidisciplinary team of machine learning experts and industry professionals from the tech, commerce, and retail sectors. This has allowed us to build software that actually serves the needs of retail planning teams and executives and enables data-driven collaboration across departments. Our mission is to break businesses free from the limitations of outdated, siloed metrics and instead, focus on high-impact growth indicators that contribute to a positive net business outcome.

Join us in revolutionizing the way that retailers interact with their data to make more accurate, granular decisions informed by both their business expertise and machine learning algorithms. 

As Analytics Lead, you'll be the first analytics hire at Flagship, playing a foundational role in shaping our data environment, metrics strategy, and customer value measurement. You’ll build the analytics layer that informs decisions across product, data science, engineering, customer success, and sales.

We're looking for someone excited to work across disciplines, comfortable with ambiguity, and passionate about building products that drive measurable value for customers in reducing waste, lowering stress, and improving online retail for independent businesses.

1. Own analytics at Flagship — from infrastructure to insights.

2. Design and implement scalable data models and metrics definitions to power our product and business teams.

3. Partner with Product and Data Science to conduct exploratory data analysis, apply statistical rigor to experiments, and validate model performance.

4. Collaborate on foundational analytics questions like: At what level of aggregation should we forecast? Are sales patterns across regions and subregions correlated?

5. Build dashboards that showcase product impact for customers and internal stakeholders.

6. Enable self-serve analytics for customer success, product, and leadership teams—empowering them with data to answer questions and drive action.

7. Work with data engineers to ensure analytics-ready data pipelines and tooling.

8. Help define how we measure customer value and shape the analytics experience for internal and external users.

• 4-7 years of experience in analytics or data science roles, with meaningful time at venture-backed startups.

• Strong foundation in statistics and exploratory data analysis—comfortable running correlation analyses, regression models, and interpreting significance in noisy datasets.

• Advanced SQL skills and hands-on experience with modern data platforms (e.g., Snowflake, Google BigQuery, DBT), version control (e.g., GitHub).

• Proven experience building analytics environments and collaborating cross-functionally with product managers, data scientists, and engineers.

• Strong communication skills—able to frame analytical findings for technical and non-technical audiences and advocate for data-driven decisions.

• Comfortable navigating ambiguity and context-switching in a fast-paced environment.

Do you have one or more of the following? Tell us about it!

• Python for deeper analysis, experimentation, or model validation

• Experience with BI tools (e.g., Tableau, Sigma, Looker, Power BI).

• Experience with supply chain, demand forecasting, or apparel production (e.g., greige goods, PFD)

Applicants must be authorized to work in the United States. Sponsorship for work visas is not available for this position.