Details of the Role

Assct. Lead Data Scientist

Location: Bangalore (Hybrid mode with 3-4 days in office), India

About the Assct. Lead Data Scientist Job Role

You will help our clients solve real-world problems by tracing the data-to-insights lifecycle: Understand business problems, making sense of the data landscape & footprint, performing a combination of exploratory, Machine Learning, & Advanced Analytics on textual data. As a data scientist, you’ll not only create and deliver innovative solutions but also guide a team of analysts. Your leadership will be instrumental in offering exceptional solutions to clients across various domains.

Qualification and experience for Assct. Lead Data Scientist GenAI & Deep learning specialization

  • 5+ years of experience in working on industrial use cases in data science using Machine Learning for measurement, forecasting, simulation, and optimization
  • Experience using AI/ML tools available from cloud service providers like Azure & frameworks like PyTorch
  • Excellent knowledge of LLM, specifically expertise in open AI skills, including GPT 3.5 and GPT 4. Experience developing solutions using AI and ML technology.
  • Proficient with deep learning algorithms, especially for developing computer vision applications
  • Excellent knowledge of FCN, CNN, DNN, and sequential neural network architectures.
  • Strong experience using basic and advanced image processing algorithms for feature engineering.
  • Ability to read and implement related academic literature and experience in applying state-of-the-art deep learning models to computer vision (e.g., segmentation, detection) or other areas such as (speech, NLP, GANs)
  • Knowledge of sensors and vision systems, sensor integration, and fusion
  • Proven expertise in developing and training state-of-the-art algorithms to perform visual recognition tasks, such as segmentation, detection, and classification at scale
  • Proven expertise in Integrating deep neural network code to run efficiently on embedded platforms, including different GPU architectures.
  • Profound and proven knowledge of tools and programming languages like TensorFlow, KERAS, Tytorch, Matlab, and Python; knowledge of embedded C/C++ is an advantage.
  • Strong experience with data science tools, including Python scripting, CUDA, numpy, sciPy, matplotlib, sci-kit-learn, bash scripting, and Linux environment.
  • Proficiency with edge computing principles and architecture on commonly used popular platforms.
  • Experience in different model optimization techniques, apart from hyperparameter tuning, to reduce memory usage without hindering performance for deploying on edge devices. BARD, Cohere, PaLM, Claude v1, etc., will be an added Advantage.

About us

We consult and deliver solutions to organizations where data is at the center of decision-making. Our products and services help make this easier by analyzing and visualizing large amounts of data. We are looking for people who can understand our capabilities and client scenarios across industries and recommend value-driven solutions to delight our customers.

To know more about us visit Gramener Website and Gramener Blog.