DATA SCIENTIST

• • Maintain and improve production algorithms; triage and fix bugs; add regression tests
• • Profile and optimize code (CPU/memory/I/O); apply parallelism/concurrency where relevant
• • Design and maintain REST APIs (Django/DRF or FastAPI) for model/algorithm services
• • Test for efficiency and scalability; benchmark latency/throughput; right-size costs
• • Ensure high code quality: unit/integration tests, type hints, CI/CD, documentation
• • Collaborate with product/data/QA to prioritize improvements and meet SLAs



• 6–8 years in data science/software roles with production-grade Python

• • Strong Python expertise (pandas, NumPy), profiling tools (cProfile, line_profiler, memory_profiler, py-spy)
• • Parallel/concurrent processing (multiprocessing, threading, asyncio) and performance tuning
• • REST API development with Django/DRF or FastAPI (auth, error handling, pagination)
• • ML fundamentals with scikit-learn; experience deploying models to services
• • Testing/quality: pytest/unit test, CI/CD, Git workflows; clear communication and documentation

• Knowledge in scikit-learn ,PyTorch or TensorFlow; experiment tracking (MLflow/W&B)

• GCP (Cloud Run/GKE, BigQuery, GCS), Docker/Kubernetes, Cloud Build/GitHub Actions

• Observability: OpenTelemetry, GCP Monitoring/Logging; Sentry

Security practices: OAuth2/JWT, secrets management, PII handling

• Opportunity to work on real production algorithms
• Exposure to high-performance Python engineering,
• Hands-on API development experience
• End-to-end model deployment exposure
• Cloud-native experience on GCP