Curriculum Vitae
Francisco Romaldo Mendes
Last updated April 2026
Expertise
Marketplace data scientist with experience in autonomous technology and hardware. Two-sided marketplace optimisation, causal inference, experimentation, real-time perception, embedded ML, sensor fusion.
Experience
Staff ML Engineer, Lyft Business
2025 – Present
- Built rider-level price elasticity framework and rewards targeting model, optimising incentive allocation under budget constraints with A/B validation (PMM, PBET).
- Built graph-based lookalike models (GCN, label propagation) over the Lyft marketplace graph for targeting, fraud, and incentives across product surfaces.
- Developed driver supply forecasting at geohash level (24h ahead) to enable forward booking for Lyft Business.
- Led causal inference on ad creatives using CV feature extraction (face, text, saliency) and propensity modelling to isolate true drivers of CTR.
Senior AI Engineer, Renesas Electronics / Reality AI
2023 – 2025
Hardware Machine Learning
- Architected multi-sensor ML pipelines across accelerometer, acoustic, voltage, pressure, and LIDAR modalities for automotive and industrial environments.
- Deployed CNN and DNN models on DRP-AI accelerators, NPUs, and MCUs; compressed via INT8 quantisation and low-rank tensor factorisation.
- Led and mentored 4 engineers; established CI, testing, and benchmarking pipelines.
Senior Data Scientist, Boston Consulting Group (BCG X / Gamma)
2022 – 2023
- Built C++ production ML pipelines (perception, forecasting, recommender systems) for latency-sensitive industrial and enterprise applications.
Research Assistant, University of Chicago
2020 – 2022
- Built a fully embedded audio perception system under 512 kB memory: segmentation, denoising, and neural inference.
Senior Data Scientist, Deloitte Consulting LLP
2016 – 2020
- Built real-time C++ anomaly detection and embedded inference pipelines for industrial and energy clients.
Technical Stack
Programming: Python, C++, MATLAB, R, Julia
Frameworks: PyTorch, JAX, TensorFlow
Deployment: ONNX, embedded toolchains, AWS, Docker
Domains: Computer Vision, Sensor Fusion, Marketplace ML, RL
Education
University of Chicago
GPA: 3.8 / 4.0
M.S. Computational Economics / Theoretical Computer Science (2022)
Indian Statistical Institute, Kolkata
Full Scholarship, Govt. of India
M.S. Statistics (Honours), QE Specialisation (2016)
