• 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.

• 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.

• Own revenue predictability, planning, and executive insight across new, renewal, and expansion revenue. • Manage and coach a Revenue Insights Analyst focused on post-sales analysis; hire and scale the team as scope grows • Own pre-sales analytics and planning personally while overseeing team output and quality • Own forecast methodology and accuracy across all revenue streams • Lead forecast cadence and executive performance reviews • Build and manage capacity models (headcount, coverage, productivity) • Lead annual and quarterly planning processes; integrate pipeline signals with planning assumptions • Lead quota and territory planning processes, ensuring capacity, coverage, and quota assumptions are aligned and data-backed • Translate performance data into actionable insight, including CAC, sales effectiveness, and full-funnel conversion/velocity across new, renewal, and expansion • Proactively flag performance risks and pipeline gaps early - before quarter-end - with clear recommended actions • Deliver executive and Board-level reporting • Build and maintain pipeline reporting (coverage, conversion, progression, aging) • Support forecast process (rollups, validation, scenarios) • Track leading indicators (pipeline creation, early-stage conversion) • Produce weekly forecast packages and dashboards • Ensure data accuracy and reporting consistency • Implement approaches to apply AI to streamline forecast modeling and scenario generation • Use AI-driven anomaly detection to surface pipeline/forecast risk earlier • Leverage AI to automate draft narratives and insights, freeing time for judgment-level analysis

• Help our CFO and chief modeller to develop new financial tools for our customers. • Elaborate ideas and develop exact numerical answers using already developed solutions as guidance. • Take these a step further, in terms of content, structure and clarity. • Cooperate closely with our team of engineers/designer(s)/product manager(s)