Perfios - Lead - Data Scientist

Description:
About the job
What your average day would look like:
- Collaborate with product and engineering teams to understand requirements and devise possible solutions.
- Explore existing research papers, ideas and codebases that can be leveraged in current tasks.
- Search for open source datasets and/or design synthetic data pipelines (including data augmentation).
- Devise and implement experiments using DL/ML models.
- Evaluate the experiments to find failure patterns and come up with improvements in data/model architecture/loss function etc.
- Communicate results and ideas to key stakeholders.
- Optimize the models for production and collaborate with software engineers for deployment.

Must have skills:
- Hands-on experience in dealing with image data and CNN based architectures
- Should have worked on deep learning frameworks (like pytorch, tensorflow, keras etc.)
- Proficient in Python and packages like Numpy, Pandas, OpenCV
- Good understanding of data structures and algorithms along with OOPS, Git, SDLC
- Mathematical intuition of ML and DL algorithms
- Good understanding of Statistics, Linear Algebra and Calculus
- Should be able to perform thorough model evaluation by creating hypotheses on the basis of statistical analyses
Highly desired:
- Hands on experience with latest computer vision model architectures and concepts like ViTs, GANs, Diffusion, Vision Language Models
- Knowledge of training and inference optimizations using CUDA, C++, ONNX, TensorRT, OpenVino etc. and profiling of ML pipelines
- Worked on building production level APIs for serving models (Flask, Django, TF Serving)
- Hands-on experience of using MLOps tools.
- Lead and mentor a team of junior data scientists and analysts, providing technical guidance, code reviews, and career development support.
- Oversee the end-to-end delivery of data science projects by coordinating with cross-functional teams and ensuring alignment with business goals.
- Manage a team of data professionals, fostering a collaborative and innovative work environment to drive analytics excellence.
- Act as a technical lead in projects, taking ownership of team deliverables, timelines, and quality assurance of data models and analytics solutions.
- Facilitate regular team meetings, set goals and priorities, and monitor progress to ensure efficient execution of data-driven initiatives.
- Collaborate with product managers, business stakeholders, and engineering teams while managing a high-performing team of data scientists.
- Champion best practices in data science, model development, and deployment while promoting a culture of continuous learning within the team