Full Stack Data Scientist & Engineer

Role Purpose: The primary goal of this role is to lead the Product-Led Growth (PLG) strategy, optimizing adoption, activation, and expansion of Mappa’s platform through exceptional user experience, product-focused go-to-market strategies, and a data-driven approach focused on key growth metrics. Key Responsibilities: Lead Product-Led Growth (PLG): Define and execute PLG strategies to ensure rapid product adoption, successful activation, and organic expansion. Collaborate closely with the Product, Design, and Growth teams to ensure that each product iteration aligns with PLG objectives. Design and Execute Go-To-Market (GTM) Strategies: Create and execute launch plans, including beta programs, launch communications, and enablement tools, all aimed at maximizing adoption and activation through user-centric experiences. Optimize the Self-Serve Funnel: Manage website messaging and the self-serve funnel, iterating with A/B testing, data analysis, and continuous conversion optimization to maximize user value throughout the lifecycle. Conduct Market and User Research: Drive research to uncover user pains, Jobs-to-Be-Done, and whitespace opportunities, with a focus on improving the product experience and driving self-expansion of users. Collaborate with Internal Teams: Work closely with Growth, Sales, and Customer Success teams to equip them with the necessary resources to support PLG growth. Help develop sales tools, decks, and objection-handling materials. Track Growth KPIs: Monitor key performance indicators related to product growth and synthesize insights for executive-level decision-making. Required Skills and Experience: PLG Experience: 3-5 years of experience working in Product-Led Growth roles within B2B SaaS or high-growth startups. Proven Record in Product Launches: Demonstrated success in launching and driving adoption of technical products, with an emphasis on organic growth through PLG strategies. Data Fluency and BI: Strong experience with PLG metrics, comfortable using BI tools for cohort analysis, funnel metrics, and data-driven decision-making. Effective Communication and Storytelling: Ability to translate complex ML/API concepts into clear, compelling messages that resonate with both users and customers. Project Management: Strong project management skills with the ability to coordinate cross-functional teams (Design, Engineering, Marketing, Sales) to deliver on tight timelines. Fluent in English and Spanish: Native-level proficiency in both English and Spanish for effective global team and client communication.

About Us We are an AI-native ecosystem that automates the backend of auto repair for workshops and parts retailers, featuring voice-activated workflows, predictive inventory, dynamic pricing, supplier matching, embedded financing tools, and an online parts marketplace. Legally incorporated in Delaware and operating out of Mexico City, our goal is to digitize, finance, and scale the automotive aftermarket in LATAM and beyond. Role Overview We’re looking for a hands-on and visionary Founding Engineer to lead the design and implementation of cutting-edge LLM and Voice System architectures. This is a full-time, remote role (preferably based in LatAm or the US) focused on building scalable AI infrastructure from the ground up. What You’ll Lead & Build: Full-stack LLM infrastructure, including prompts, embeddings, and vector databases (e.g., Pinecone, Weaviate) Scalable, multilingual RAG systems trained on real-world case data Voice-to-intent pipelines using Whisper or more advanced tools Intelligent, tool-using agents for diagnostics, repair, and procurement tasks GEO (Generative Engineering & Operations) systems — including agent orchestration, contextual memory, and feedback loops Real-time performance optimization across voice, text, and structured data Full lifecycle ownership — from prototypes to market-ready production systems You’re a Great Fit If You: Bring 7+ years of experience in ML/NLP, with 2+ years in generative AI Have led architecture and scaling of agentic or multimodal AI systems Have successfully launched LLM-powered products to production Know tools like LangChain, LlamaIndex, and vector databases deeply Have real-world experience deploying effective RAG pipelines Prioritize latency, user experience, and cost-efficiency Are fluent in English (Spanish/Portuguese is a plus) Thrive in fast-paced environments and want to shape a global product at scale

About Mappa Mappa builds real-time voice-AI infrastructure that decodes over 100,000 behavior patterns per person—based on prosodic and linguistic signals—and turns them into actionable insights for hiring and beyond. Our data science team transforms raw audio into structured understanding at scale. Role Purpose Analyze and model complex behavioral and audio data sets to power Mappa’s AI systems. You’ll design and implement data pipelines, extract actionable insights, and prepare datasets for training cutting-edge machine learning models. Key Outcomes (First 6 Months) Deliver at least 3 key insights from exploratory analysis that inform product or model design. Build and deploy at least one production-grade ML-ready dataset using Airflow. Identify and implement ≥ 2 performance improvements in existing data pipelines. Collaborate with ML and Product to define data strategies for new features or behavior signals. Core Responsibilities Analyze voice, text, and behavioral datasets using statistical and ML methods. Prepare, clean, and transform data for downstream machine learning tasks. Design and maintain data pipelines using Airflow and Dockerized workflows. Contribute to model development using tools like Hugging Face and PyTorch. Collaborate with ML Engineers and Product to align data initiatives with product goals. Present findings and prototypes to cross-functional stakeholders, including CTO and COO. Monitor data health, quality, and coverage across all stages of the pipeline. Must-Have Skills 3–5 years in data science, ML, or analytics with experience in real-world data problems. Proficiency in Python and ML/data libraries (e.g., pandas, scikit-learn, Hugging Face). Experience building and maintaining data pipelines with Apache Airflow. Familiarity with Docker and modern data architecture principles. Strong foundation in statistics, data wrangling, and model evaluation. Comfortable communicating complex results to non-technical stakeholders. Fluent in English. Nice-to-Have Experience with audio, voice, or behavioral datasets. Familiarity with time-series analysis or sequence modeling. Knowledge of vector embeddings or NLP model fine-tuning. Who You Are A curious and rigorous thinker who’s fluent in data and comfortable navigating ambiguity. You love turning messy signals into structured insight—and insights into products. You value reproducibility, impact, and collaborating with multidisciplinary teams. Why Join Mappa Deep impact: Your insights shape the core of our AI product. Modern stack: Work with Python, Hugging Face, Airflow, and Docker in a fast-moving team. Remote-first: Join a distributed team across LatAm and the U.S.