• Partner with Solution Architect, Sales Strategy, Ecosystem, and other Go-To-Market stakeholders and teammates to translate questions about pre-sales engagement, consumption, pipeline, and sales efficiency into clear analytical requirements. • Design and build AI and analytic solutions that provide actionable insights for trial management, win rates, adoption, conversion, and overall sales metrics. • Craft well-structured, maintainable solutions in both business intelligence and AI tools that follow internal standards and make it easy for customer-facing teams to monitor performance and take action. • Partner with operational and data teams to define requirements for stakeholders and engagement data models, shaping how data is collected, structured, and made available for analysis. • Use segmentation, cohort analysis, and experimentation techniques, such as A/B testing, to inform scaled engagement strategies and forecast the impact of digital programs. • Serve as a subject matter expert in sales analytics by sharing best practices, documenting logic and methodologies, and providing guidance to help partners and other analysts use data to make better decisions.

• Analyze customer implementation data, product usage patterns, and lifecycle metrics to identify new areas of impact and clinical value. • Build and maintain dashboards that track Go Live performance, time-to-value benchmarks, and early indicators of customer engagement. • Quantify the impact of configuration decisions, workflow design, and feature utilization on customer outcomes. • Identify trends and recurring friction points across deployments, translating them into structured insights for Operations and Product teams. • Collaborate with Clinical Product to surface real-world deployment insights that inform roadmap prioritization and feature refinement. • Work with Sales and Customer Success to develop evidence-based narratives around product value and operational impact. • Work with the Marketing team to evaluate communication opportunities, shape messaging based on real-world product impact, and support the development of relevant content and thought leadership. • Support leadership with structured analysis to guide strategic decisions around customer segments, workflows, and growth opportunities.

• Praxisnaher Unterricht: Du gestaltest ein hybrides Trainingsformat - 2 Tage Präsenz / 3 Tage Remote direkt an der Spree in Berlin-Kreuzberg. • Wissensvermittlung: Du vermittelst alle relevanten Inhalte praxisorierentiert - Python, Datenbanken, Statistik, Machine Learning oder BI-Tools. • Teilnehmerinnen-Begleitung: Du betreust die Teilnehmenden durch regelmäßiges Feedback & unterstützt ihre Lernfortschritte fachlich ideal. • Zertifizierungen: Du bereitest unsere Teilnehmenden für die jeweiligen Module auf alle relevanten Zertifizierungen vor. • Motivation: Du schreibst Empowerment groß & schaffst so eine offen unterstützende Lernumgebung für unsere Teilnehmenden im Tech-Bereich. • Module (Einsatz je nach Expertise): Python Programmierung (Einführung bis Fortgeschrittene objektorientierte Programmierung), Vorbereitung auf die Zertifikatsprüfungen des Python Instituts (PCEP, PCAP und PCPP1), Datenanalyse mit Python (PCAD Zertifizierung), Datenbanken, SQL (Zertifikat: DP-900), KI Grundlagen für Data Science (Microsoft AI-901 Zertifizierung), Microsoft Tech Stack: MS Power BI (PI-300), Datenarchitektur & Data Platforms (DP-600 / Fabric).

• Build and maintain reporting, dashboards, and analytics tools helping sales leaders and frontline teams understand performance, prioritize work, and identify growth opportunities. • Develop scalable analyses across sales execution, pipeline health, account prioritization, market coverage, territory performance, sales productivity, and growth planning. • Translate ambiguous business questions into structured approaches, insights, and recommendations for stakeholders. • Create decision support tools surfacing whitespace, high-priority accounts, coverage gaps, outreach penetration, funnel performance, and execution opportunities. • Conduct TAM, segment, and coverage analyses guiding leadership investments and scaling. • Own Retail’s territory analytics and operating infrastructure: design, account coverage, reporting, and maintenance. • Migrate manual workflows into scalable systems across Salesforce, Snowflake, and Sigma. • Develop territory visualization and mapping tools giving sales teams visibility into market coverage, prospect density, whitespace, and prioritization opportunities. • Partner with sales leadership to evaluate territory models, coverage, capacity, equity, and expansion opportunities. • Develop coverage strategies for new Retail segments and geographies as the business expands. • Build SQL/Python automations improving data quality and reducing manual work across data flows, scoring models, monitoring, and reporting. • Manage territory data loads, mapping configurations, and system updates with central operations and tech teams. • Build and maintain scalable enrichment workflows cleaning, classifying, and enhancing prospect and account data using LLMs. • Develop territory and account prioritization models using sales performance, volume potential, market characteristics, business attributes, and field capacity. • Own third-party market data strategy: vendor evaluation, procurement support, relationship management, and data quality oversight. • Build automated tools monitoring Rules of Engagement (ROE) exceptions, partnering with central governance to improve compliance workflows and automate resolutions. • Represent Retail’s territory data and infrastructure needs with cross-functional GTM partners across adjacent Business Technology, Data Infrastructure, and Finance. • Manage a roadmap of territory infrastructure enhancements based on impact and scalability. • Serve as Retail SME on territory operations, market coverage, account prioritization, and territory analytics.