Data Scientist Lead

Purpose & Scope: As the Data Science Lead (coordinator), you will lead a team of data scientists and scientific software developers within our Rio de Janeiro R&D hub, working as one team with TGS Data Science in Houston. You will set the technical direction for developing, scaling and supporting TGS’s AI and data technologies: ML-driven processing and interpretation, the MDIO open-source data format and the TGS Data Verse platform — on GPU and CPU HPC clusters and in the cloud.

Your primary objective is to turn research into robust, high-performance software that TGS and its clients rely on, in support of the TGS Data-AI strategy (AI for Growth).

Responsibilities

Lead, mentor and grow a team of data scientists and scientific software developers, setting clear technical goals, coding standards and development paths. Technical Direction: Define the architecture of ML models, data pipelines and HPC/cloud workflows in line with the TGS Data Science roadmap in Houston — one shared codebase and toolset.

AI Development: Oversee the design, scaling and validation of deep learning models for seismic processing, imaging and interpretation, from seismic foundation models (ViT) to 3D CNNs such as Salt. Net. Performance & Scalability: Drive the profiling, parallelization and optimization of training and inference on GPU and CPU clusters (CUDA, MPI, multi-node) and on AWS, keeping compute efficient and costs under control.

Data Platforms: Champion MDIO and cloud-native data practices — chunked, compressed data accessible in place — and integration with TGS Data Verse (Data Lake, OSDU) and Prediktor operational data. Production Readiness: Own the path from prototype to product — packaging, testing, CI/CD, model registry and deployment into TGS production software (e.

g., Imaging Any. Ware) and HPC environments. Engineering Excellence: Establish best practices across research and production code: clean architecture, code review, automated testing, documentation and reproducible experiments. User & Business Support: Partner with geophysicists, imaging, HPC/IT and product teams to turn needs into requirements and to support users of TGS AI and data tools across the energy data value chain.

Innovation & Representation: Track advances in AI, HPC and data technology; drive open-source contributions (e.g., MDIO), patents and publications; represent TGS in technical forums.

Education

& Experience Education: Bachelor’s/Master’s degree in Geophysics, Physics, Computer Science, Applied Mathematics, Engineering or a related field, including 5+ years leading R&D or software projects. Leadership Experience: 3+ years leading data science, research or scientific software teams, with a track record of delivering software to production.

Technical Experience: Expert Python (Num. Py, Sci. Py, Py. Torch) and modern C/C++; Fortran is a plus. Highly experienced with MPI, CUDA, OpenMP or other parallel programming models on GPU and CPU HPC architectures. Highly experienced in debugging, profiling and optimizing scientific code (e.g., Nsight, perf, VTune). Distributed training and inference of deep learning models (DDP/FSDP, mixed precision) and MLOps practices (experiment tracking, model registry, deployment).

UNIX/Linux and POSIX programming, Git, automated testing and CI/CD. Data & Infrastructure: Multidimensional, chunked data formats (MDIO, Zarr, SEG‑Y) with Dask/xarray; AWS (S3, EC2 GPU); containers (Docker, Kubernetes); HPC schedulers (e.g., Slurm). Domain Expertise: Experience with seismic processing, imaging or interpretation algorithms; publications or patents in ML, HPC or geophysics are a strong advantage.

Desirable: OSDU data platforms and master data management; industrial time-series data and OPC UA; contributions to open-source scientific software (e.g., MDIO). Languages: Fluent English and Portuguese Work arrangement & Location: Presential, based in Rio de Janeiro – RJ, with Brazilian residency and work authorization, and available for occasional travel.