Do you thrive at the intersection of data, strategy, and real business impact? Freebird® is a high-growth DTC brand redefining shaving for millions of people. We’ve scaled to 9-figures in revenue, served over 2 million customers, and built a reputation for performance-driven creative and disciplined execution. We’re looking for a Director of Growth Analytics to build and lead the measurement engine that powers our next phase of profitable growth. This is role at the core of our growth strategy. You will own the systems, frameworks, and insights that determine where we invest, where we pull back, and how we scale efficiently. Your work will directly influence budget allocation, CAC targets, contribution margin performance, and long-term LTV expansion. You will partner closely with Paid Media, Creative Performance, Ecommerce, Retention, and Executive Leadership to ensure decisions are grounded in trusted data and tied to financial outcomes. What You’ll Do Own the Growth Measurement Foundation - Ensure tracking and attribution integrity across ad platforms, GA4, server-side events, and ecommerce systems. - Implement monitoring and alerting to proactively catch data breaks, attribution shifts, and pipeline failures. - Establish clear UTM governance and campaign standards to maintain clean, scalable reporting. - Partner with platform owners and Engineering to continuously improve data quality and reduce blind spots. Lead MMM, Incrementality, and Budget Decisioning - Define and own the roadmap for MMM, MTA, and incrementality testing. - Establish testing standards, learning agendas, and clear decision rules for budget allocation. - Translate model outputs into actionable recommendations on where to invest, reduce spend, or test new opportunities. - Build organizational trust in causal measurement so decisions are not driven solely by platform-reported metrics. Build a Centralized Source of Truth - Stand up and evolve a unified data foundation across acquisition, ecommerce, retention, and finance inputs. - Standardize metric definitions and ensure teams operate from one trusted set of numbers. - Partner with Finance to align on revenue, discounts, refunds, COGS, and contribution margin calculations. - Document data ownership and governance to improve reliability and speed of decision-making. Deliver Full Funnel Visibility - Create end-to-end visibility from first touch through repeat purchase. - Connect channel, audience, creative, and offer performance to downstream outcomes such as refunds, retention, and contribution margin. - Identify bottlenecks and quantify the highest leverage growth opportunities across the funnel. - Provide forecasting inputs that support budget planning and scenario modeling. Build Insight Loops That Drive Action - Develop automated daily and weekly reporting that supports the growth operating rhythm. - Deliver dashboards and alerts that flag pacing risks, efficiency shifts, and emerging opportunities. - Provide recurring performance narratives explaining what changed, why it changed, and what to do next. - Ensure insights convert into concrete actions, test plans, creative briefs, and accountable follow-ups.

About Veho Veho is on a mission to revolutionize the post-purchase experience. We’re building a new, end-to-end logistics infrastructure—from middle mile to last mile—powered by tech that puts customers first. By removing the pain points in delivery and returns, Veho creates deeper loyalty and trust between brands and their customers. Our rapidly growing client list includes leading consumer brands like Hello Fresh, Zara, Macy’s, Sephora, and more. We’re proud of our championship culture, best-in-class benefits and the chance for every team member to share in our success through equity. Whether you work at one of our facilities or remotely, at Veho you’ll join a mission-driven team that’s transforming logistics—and having a lot of fun along the way. About The Role: As a Data Scientist, you’ll be part of a team of Data Scientists to help define, build, and operate sophisticated models to answer hard questions centered around improving our logistics network and user experiences. In particular you will be focused on the Last Mile space to better understand our driver’s delivery behavior and improve our tools for creating, estimating, and tracking routes. You’ll partner with product managers to understand high-value business problems, build systems that inform daily operations, and work with cutting-edge technology. You’ll work closely with software engineers to operationalize the models you build in the production systems that drive Veho. Responsibilities Include: - Building reliable, efficient, and scalable Data Science models - Using telemetry data to understand how we can help drivers deliver our packages more efficiently - Creating data products that help stakeholders understand company performance in the area of Last Mile - Understanding business context and gathering requirements - Proactively identifying the most impactful opportunities to shape product roadmaps - Creating robust data pipelines to feed analyses and models - Analyzing and evaluating the impact and effectiveness of models in production systems What You Bring: - Bachelor’s Degree plus 4 years of experience in data science or data engineering, or Master’s Degree plus 2 years in data science - At least 2 years of experience using statistical modeling or machine learning techniques to solve business problems. - Strong SQL and Python skills are a must - At least 2 years of experience with open source languages and tooling used for large-scale data analytics like Python, numpy, and/or distributed data processing systems like spark - At least 2 years of experience with analytical relational databases like Redshift, BigQuery, or Snowflake - At least 2 years of experience working with cloud-based data engineering and data science tools. - Experience with MLOps and model deployment pipelines - Experience building models in supply chain or logistics (telemetry data insights, volume and capacity forecasting, route building) to generate insights is a plus. Compensation: $120,000-135,000 per year The pay range is subject to the discretion of the Company. Additionally, Veho offers a competitive equity package, comprehensive medical, dental, and vision coverage as well as other benefits such as 401k and generous PTO for full-time roles. Veho is a growth company that looks for team members to grow with it. Veho offers a generous ownership package, casual work environment, a diverse and inclusive culture, and an electric atmosphere for professional development. No matter the location, or the role, every Veho employee shares one galvanizing mission: driving commerce forward with a customer-centric delivery and returns experience that’s built for the modern era. We are deeply value-driven (Team Up, Drive Impact, Take Ownership, Solve Bigger, Obsess Over Experience, Make Today Count) and care tremendously about investing in people. We are committed to creating a diverse team and an environment that provides everyone with the opportunity to do the work of their lifetime. Veho is unable to provide sponsorship at this time. Veho is committed to nurturing, cultivating and preserving a diverse and inclusive work environment. Empathy and respect for each other is core to our values and a central part of working here every day. The diversity of our employees, drivers and applicants is welcomed and encouraged. All California applicants please reference our California Applicant Privacy Notice located here.

• Develop and implement machine learning models and solutions. • Collaborate with cross-functional teams to drive AI initiatives. • Optimize and enhance ML systems for scalability. • Lead discussions with stakeholders regarding AI strategies and solutions. • Mentor junior team members in ML best practices.

• Analyze large, complex datasets to identify abuse patterns, fraud signals, and harmful behavior trends. • Conduct root cause analysis to diagnose safety incidents and emerging risks. • Evaluate new tool effectiveness (including AI), and impact on agent efficiency and user satisfaction. • Define and track core metrics (e.g., harm prevalence, violation rates, detection accuracy). • Navigate the tradeoff between operational efficiency, safety, and user growth/experience. • Build dashboards and reporting frameworks to track platform health and safety performance. • Develop heuristics, statistical models, and machine learning solutions for proactive detection of abuse, fraud, or harmful content • Build prediction systems (e.g., anomaly detection, risk scoring, behavioral profiling). • Improve automated enforcement and moderation workflows. • Evaluate model performance and iterate on detection strategies. • Design and analyze experiments (A/B tests, causal inference) to measure safety feature impact (e.g., login & verification, AI moderation support). Clearly communicate findings to technical and non‑technical stakeholders. • Quantify tradeoffs between operational efficiency, safety, and user growth/experience. Guide TnS team on key tradeoffs in decision-making • Partner with Product, Engineering, Operations, Policy, and Legal teams to define safety strategy. • Influence decision-making through data storytelling and insights. • Standardize analytical methodologies and tools for scalable decision-making.