Senior Data Strategist

Senior Data Strategist (Client facing + Technical Reporting) Join to apply for the Senior Data Strategist (Client facing + Technical Reporting) role at Braintrust. We are seeking a Senior Data Strategist who will serve as a strategic advisor, technical expert, and hands‑on analytics practitioner supporting Servant’s clients and internal teams. This role bridges high‑level data strategy, technical execution, and client‑facing communication, ensuring Servant delivers excellence in analytics, reporting, and data‑driven decision‑making. The individual will play a key role in our Customer 360 initiatives and broader Analytics Center of Excellence (ACoE), supporting areas such as Product, Marketing, Donor Development, Operations, and Finance. This position is an immediate, part‑time, project‑based role approved for 20 hours per week over an initial 3‑month period, with potential to extend or increase hours based on client needs. Key Responsibilities Strategic Data Leadership Serve as a strategic partner to internal and external stakeholders, translating business needs into analytical frameworks, reporting strategies, and data‑driven recommendations. Lead technical execution across analytics workflows, guiding junior analysts and partnering closely with the Data Architect and Data Governance leads. Own the roadmap for analytical maturity, operational efficiency, and reporting excellence across client engagements. Educate clients on best practices, helping them become more self‑sufficient with data literacy and interpretation. Client Engagement & Communication Interface directly with clients to gather requirements, present insights, guide decision‑making, and build trust in Servant’s technical solutions. Tell compelling stories using data—turning complex datasets into clear, actionable, and strategic recommendations. Ensure a seamless client experience across all reporting, analytics, and Customer 360 workstreams. Present insights, trends, and recommendations in a way that resonates with executives and non‑technical stakeholders. Advanced Analytics & Statistical Modeling Conduct statistical modeling including regression, forecasting, survival analysis, clustering, and predictive scoring. Build and evaluate machine learning models to predict likelihood to churn, convert, or donate. Design and analyze A/B tests and controlled experiments to support product, marketing, and operational decision‑making. Perform cohort analysis, retention modeling, segmentation, and donor lifecycle analytics. Product User & Experience Analytics Analyze user behavior, feature adoption, funnel performance, and engagement trends to identify strategic opportunities. Conduct UI/UX analytics including clickstream, heatmaps, user flow mapping, and conversion optimization. Partner with Product and Design teams to provide insights that improve user experience and drive growth. Cross‑Functional Business Insights Support Marketing with campaign analysis, audience segmentation, conversion trends, and growth forecasting. Provide operational and financial insights using donor data, revenue models, cost efficiency metrics, and forecasting. Deliver donor development analytics including retention, lifetime value, and giving behaviors. Technical Execution & Data Engineering Write advanced SQL to extract, model, and explore datasets from Snowflake, BigQuery, and other cloud data warehouses. Use Python for wrangling, statistical analysis, prototyping ETL workflows, automation, and modeling. Build scalable, automated analytics workflows that minimize reliance on Data Engineering. Ensure data accuracy, consistency, and validation within reporting pipelines. Reporting, Dashboards & Visualizations Design intuitive dashboards in Power BI, Tableau, or custom BI tools to surface KPIs, trends, and insights. Create executive‑level reports that support weekly, monthly, and quarterly business rhythms. Automate manual reporting processes for reliability and real‑time visibility. Continuously evolve dashboards and reporting layers based on business needs and stakeholder feedback. Data Quality, Governance & Integrity Partner with the Data Architect and Data Governance lead to ensure consistent data standards and clean data flows. Implement proactive data validation, discrepancy detection, and quality monitoring. Advocate for data consistency, documentation, and trusted sources of truth across the organization. Qualifications Bachelor’s degree in Data Science, Analytics, Statistics, Computer Science, or a related field (or equivalent experience). 5+ years in hands‑on analytics roles spanning product, marketing, donor, finance, or operations analytics. Strong client‑facing experience with the ability to distill complex information into clear insights. Advanced proficiency in SQL (complex queries, modeling, optimization) Python (analysis, automation, modeling, scripting, ETL) BI & visualization tools (Power BI, Tableau) Product/UX analytics platforms (GA4, Amplitude, Mixpanel, etc.) Demonstrated experience with Statistical modeling & predictive analytics Machine learning for classification/regression A/B testing methodologies Forecasting and growth modeling Large‑scale datasets using Snowflake, BigQuery, or similar Consulting & Leadership Skills Proven ability to lead analytic workstreams and guide junior analysts. Strong communication, storytelling, and client relationship skills. Ability to convert ambiguous client requirements into structured analytical plans. Highly resourceful, self‑sufficient, and proactive—able to operate end‑to‑end. Attributes Highly detail‑oriented with a strong commitment to accuracy. Strategic thinker with a bias for actionable execution. Adaptable in fast‑paced environments with shifting priorities. Comfortable working remotely and available 10–2 EST for client communication. Preferred Experience with donor analytics, nonprofit models, or recurring giving programs. Prior consulting experience. Experience working with Customer 360 initiatives. Employment Type Part‑time #J-18808-Ljbffr