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🗣️🇧🇷🇵🇹 Portuguese Required
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• Continuously monitor the SaaS + fintech ecosystem for healthcare: Rivio, Upflux, Osigu, Noxtec, TOTVS Saúde and new entrants • Build and operate an active monitoring system with defined sources, update cadence and output format — not ad-hoc research • Use AI to scale monitoring: news-tracking agents, competitor job boards, reviews and industry publications • When a competitor releases a feature, changes pricing, enters a Fin-X account or receives funding — you deliver the context to the Director before the market notices • Own the win/loss process — from playbook design to quarterly synthesis with actionable patterns • Conduct structured interviews with prospects and lost customers, neutrally and without commercial-executive bias • Categorize loss reasons by dimension: product, price, sales process, timing, competition and inertia • Automate transcription and categorization with AI to identify clusters and patterns at scale • Maintain an up-to-date map of the Brazilian hospital TAM (Total Addressable Market): networks, independents, by size, specialty and region • Cross-reference with the current customer base to identify whitespace — where Fin-X is not yet present but should be • Feed Commercial Planning's territory planning with structured data, not estimates • Automate collection of public data: CNES, ANS and hospital industry publications • Keep market share up to date and identify market opportunities • Map the TAM of the installed base: for each customer, what revenue headroom remains uncaptured — which products they don't use, how many units are not yet deployed, and potential take rate • Produce an upsell-readiness model: which customers have the profile, health and timing for expansion — combining product adoption, health score and financial behavior • Identify churn-risk signals in advance: drops in adoption, atypical financial behavior, stakeholder changes — before CS sees the problem • Deliver a prioritized monthly list of expansion candidates to CS and Sales — with estimated revenue potential and a recommended outreach window • Provide CS with risk intelligence: prioritized monitoring accounts with context for why they are on alert — not just the score, but the signal that generated it • Collect and maintain market benchmarks: typical win rate for B2B SaaS in healthcare, sales cycle by company size, take rate of health fintechs, NRR of similar platforms and signals that feed the product roadmap • When the Director needs to know if Fin-X's pricing is correct or if churn is above expectations — you have the benchmark • Identify market signals that inform the roadmap — recurring demands in win/loss, competitor features gaining traction, gaps that generate systematic loss • Produce quarterly cohort analysis that validates or questions the current ICP: which customer vintages have higher LTV, lower churn, greater expansion • Identify what the best customers have in common — and what the worst have in common — to refine qualification criteria • Supply Commercial Planning with an evidence-based ICP, not intuition • Build and operate competitive monitoring agents that deliver a structured weekly digest to the Director • Use LLMs (GPT-4, Claude) to process and synthesize large volumes of interviews, reviews and documents • Implement automations with low-code tools (Zapier, Make, n8n) to collect and structure market data • Build simple predictive models with low-code ML tools to support expansion and ICP decisions • Keep an external intelligence dashboard automatically updated — share of voice, competitive movement, evolution of the TAM
• Degree in Business Administration, Economics, Engineering, Data Science or related fields — the degree matters less than analytical and synthesis ability • Experience across at least two of the following contexts: strategy consulting, competitive intelligence at a technology company, B2B market research, strategy/planning in SaaS, or commercial BI • Exposure to the healthcare sector is a plus — but not a blocker if the analytical profile is strong • Advanced Excel / Google Sheets: modeling, pivot tables, cohort analysis • Basic to intermediate SQL: able to extract and join data without depending on engineering • Practical use of AI at work: GPT-4, Claude, Perplexity — not as a curiosity, but as a daily tool • Low-code automation tools: Zapier, Make or n8n — for building flows without developer support is a plus • Qualitative research methodology: interview script design, unbiased conduct, structured synthesis • Structured curiosity: does not get lost in endless research — defines what needs to be known, searches efficiently and delivers insight • Tolerance for ambiguity: works well with partial data and communicates the confidence level of deliverables • Executive communication: turns complex analysis into three slides the CEO understands and can act on • Autonomy and proactivity: does not wait to be asked — monitors the market and surfaces signals before the question arises • Intellectual flexibility: changes hypotheses when data contradicts them — does not defend the analysis, defends the truth • Systems thinking: understands that intelligence serves decision-making, not reporting — the goal is impact, not volume of output • Basic Python: for collection automations, data cleaning and simple scripts • Visualization tools: Power BI, Looker Studio or similar • Predictive modeling with low-code ML platforms (DataRobot, BigML or equivalent) • Basic web scraping for public data collection
• Performance reviews: growth based on your development • Onboarding kit • Fin-X Day: a semiannual gathering for Culture & Strategy alignment • Access to Fiibo: exclusive perks to make daily life easier • Welhub: a wellbeing platform to support your physical and mental health • Company recess
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