• Support high‑impact analytics initiatives from problem framing through delivery; quantify value, design robust analyses, and communicate recommendations to business partners and executives • Partner with business leaders to identify analytics opportunities and deliver actionable insights. Present findings and recommendations to partners and leadership in clear, compelling formats • Develop analytics products and solutions using Databricks, modern Business and Artificial Intelligence tools and Agile principles • Implement advanced analytics where applicable, leveraging Python for advanced analytics, automation, and integration with Databricks workflows • Architect and publish trusted Power BI datasets and dashboards (DAX, Power Query, semantic models), following standards for usability and adoption • Build performant Databricks workflows (notebooks, jobs, SQL Warehouses) to wrangle large datasets, engineer features, and automate recurring analyses • Develop Python scripts for automation, data wrangling, and integration with Databricks and Azure services • Partner with Data Engineering for scalable data solutions • Own analysis quality: data validation, experiment/study design, sensitivity checks, and reproducibility (versioning, documentation) • Define and monitor KPIs; create and make improvement recommendations based on scorecards and operational reporting that tie directly to business objectives • Demonstrate advanced and compelling data storytelling, statistical thinking, and visualization craftsmanship • Collaborate with Data Governance and Compliance to ensure appropriate use of PHI and adherence to privacy/security controls • Facilitate data stewardship and literacy across the business • Drive adoption of data products to scale data value • Stay current with emerging analytics methodologies, technologies and capabilities and apply for continuous improvement

• Support research and analysis efforts related to mobility, data analytics, and innovative transportation technologies • Contribute to the development, testing, and refinement of data-driven tools, platforms, and internal applications • Apply programming, data analytics, and technical skills to support analytical workflows, automation, and innovation-focused initiatives • Support data visualization and storytelling efforts to translate technical findings into clear, accessible insights for a range of audiences • Collaborate with project teams across transportation disciplines to support ongoing tasks, special analyses, and ad-hoc project needs • Document methods, findings, and lessons learned in a manner that balances technical rigor with clarity for non-technical stakeholders

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description Little Spoon was founded on the belief that today’s parents are different – equal parts more time-strapped and more food-savvy than ever. We set out to disrupt a century-old category with products and an experience that delivers on what the modern parent deserves. And we’re at a very exciting growth stage— we’re the #1 online baby and kids food brand in the US, and made our foray into retail last fall - nationwide at Target! As we continue to scale, we’re looking for a Manager, Strategic Analytics (Customer Engagement) to provide actionable insights as we work to constantly improve our retention strategy. This isn't a role for someone who just wants to "watch" the data; you’ll be in the driver’s seat. You’ll report to the Director of Strategic Analytics, but you’ll work cross-functionally with teams across the company to help improve the customer experience. You will turn complex behavioral patterns into the roadmap that keeps our customers engaged. From cracking the code on churn to optimizing the customer journey, you’ll bring the rigor and speed needed to make sure every Little Spoon family has a seamless, joyful experience. What You’ll Do - Be the Strategic Partner: Act as the primary analytics partner for the Customer Engagement group, working across Lifecycle Marketing, Digital Product, and other teams to translate business questions into data-driven roadmaps. - Drive Retention & Engagement: Apply statistical modeling techniques, such as regression, to identify behavioral drivers of churn and surface actionable opportunities to improve customer lifetime value (LTV). - Own the Data Lifecycle: Manage and update dbt models to ensure our customer engagement data is clean, reliable, and ready for analysis. - Build Intuitive Dashboards: Build and maintain high-impact Omni dashboards that move beyond vanity metrics, providing teams with the data and insights they need to succeed. - Champion Experimentation: Lead the design, execution, measurement, and socialization of A/B tests aimed at increasing engagement and reducing churn. - Influence Strategy: Deliver clear, compelling "so what" insights to leadership, ensuring that every strategic decision is backed by rigorous data and a deep understanding of our customers. What You’ll Bring - A Strategic Mindset: You don’t just pull reports; you define the right questions to ask and can connect data to real-world business outcomes. - Full-Stack Analytical Skills: You are comfortable moving from raw data in BigQuery, to transformed models in dbt, to insightful dashboards in Omni. - A Bias for Action: You thrive in a fast-paced environment and have a pragmatic approach to analysis that balances speed with accuracy. - Data Storytelling: The ability to translate complex statistical concepts into clear, actionable narratives for non-technical stakeholders and executives. - Collaboration & Curiosity: You are a strong partner for your cross-functional teams, known for your proactive problem-solving and desire to dive deep on the details of customer behavior. What You’ll Need - 5-7+ years in data analytics, with a strong track record of business impact at DTC, eCommerce, or subscription-based business. Experience with website / digital product analytics and a history of successfully generating actionable insights from web and product event data. - Expert-level SQL and experience managing data transformations within dbt. - Obsession with leveraging AI to move faster and smarter, and experience experimenting with and using AI tools (Claude, Devin, Pecan, etc.) to be a force multiplier for efficiency and insights. - Modern Data Stack Knowledge: Hands-on experience with BigQuery (or similar cloud data warehouses) and a passion for building scalable data models. - Visualization Expertise: Experience building intuitive, high-impact dashboards and explorations in Omni (or similar tools like Looker or Tableau). - Statistical Foundation: Strong grasp of statistical significance and extensive experience supporting rigorous A/B testing. Working knowledge of regression modeling, including how to control for confounding effects. Nice to Have - Email Data: Experience with analyzing email campaign data, like Braze, to help inform improvements to communications. - Python / R: Ability to use Python / R to create statistical models that synthesize patterns in our data into actionable narratives. Benefits - Equity: Every Spooner shares in our success. All full-time salaried employees are granted stock options as part of their total compensation. - Comprehensive Health Coverage: We offer medical, dental, and vision plans with a variety of options to fit your needs. - 401(k) with Company Match: We match 100% of your contributions up to 5% of your salary — with no waiting period. - Flexible PTO + Holidays: In addition to 11 company holidays, we offer flexible paid time off (no set cap) for full-time employees. - Paid Parental Leave: We’re proud to support new parents with at least 12 weeks of paid leave (and up to 18 weeks for birthing parents). Available after 6 months of full-time employment. - Learning & Development: $250 per quarter to invest in your growth — whether that’s coaching, courses, or your next great read. - Little Spoon Perks: $200 Welcome to the Team credit, 50% off recurring code for your own account, 20% off recurring code to share with close friends & family.

• Explore blockchain ecosystem to detect possible opportunities and risks • Optimise economy for validation process including research, modelling, improving business processes. • Design and develop end-to-end data solutions, from initial analysis and model development to deployment, optimizing for performance and scalability • Provide informative dashboards to team, company and community. • Configure data platform instruments to load, process and transform data • Formulate data requirements for data engineering team. Decide on granularity, frequency, data quality. • Govern your team data marts. Provide data lineage from sources to reporting. • Provide ad-hoc support to your team