• 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).

• Develop scalable analyses across sales execution, pipeline health, account prioritization, market coverage, territory performance, sales productivity, and growth planning. • 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. • 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. • Translate ambiguous business questions into structured approaches, insights, and recommendations for stakeholders. • Design and execute advanced territory models that optimize sales coverage, ensure rep equity, and maximize market penetration across new retail segments and geographies. • Lead the annual and mid-year territory carving processes, translating leadership’s high-level capacity targets into balanced, data-driven books of business. • Develop territory visualization and mapping tools giving sales teams visibility into market coverage, prospect density, whitespace, and prioritization opportunities. • Partner directly with sales leadership to evaluate territory health, diagnosing under-covered markets, capacity bottlenecks, and expansion opportunities. • Conduct TAM, segmentation, and propensity-to-buy analyses to guide leadership on where to deploy the next dollar of sales investment. • Migrate legacy territory planning workflows into scalable systems across Salesforce, Snowflake, and Sigma. • Build SQL/Python automations to improve data quality, automate scoring models, and streamline account-to-territory routing. • Manage territory data loads, mapping configurations, and rule exceptions in partnership with central business technology teams. • Enrich and classify prospect data using LLMs and third-party data vendors to sharpen our account prioritization models. • Serve as the Retail SME on market coverage, rules of engagement (ROE), and territory analytics. • Build automated tools monitoring ROE exceptions, partnering with central governance to improve compliance workflows and automate conflict resolutions. • Measure territory productivity, providing leadership with dashboards that track pipeline health, quota attainment by territory type, and outreach penetration.

• Work on training and evaluating models and prompts, fine-tuning, optimization of chunking and tokenization, bias detection, adversarial prompt testing, and selection of embeddings (supporting RAG); • Train and evaluate generative AI models, including LLMs and multimodal models; • Develop and optimize prompts, including adversarial testing and risk mitigation; • Perform fine-tuning and hyperparameter tuning to maximize performance; • Implement chunking and tokenization strategies for efficiency and quality; • Detect and remediate biases in data and models, ensuring ethical compliance; • Select and validate embeddings for RAG (Retrieval-Augmented Generation) applications; • Monitor quality, robustness, and safety metrics for models; • Collaborate as a subject-matter specialist with engineers and architects to securely integrate models into production pipelines.