Data Scientist

About KnowDis

KnowDis is an AI-driven company based in Delhi dedicated to transforming e-commerce and banking sectors through cutting-edge technology. With expertise in artificial intelligence, machine learning, and large language models (LLMs), we develop innovative solutions that enhance operational efficiency and drive growth. In e-commerce, we build advanced systems for product search optimization, leveraging LLMs to improve natural language queries and search accuracy.

Our team includes B.Tech and Phds from various IITs including Delhi, Guwahati, BHU. Across both industries, we are committed to delivering intelligent, scalable AI solutions that shape the future of business and finance.

About the Role

At KnowDis, you will move the world forward. Every day, we create innovative machine-learning solutions to help our clients across e-commerce, healthcare, and finance domains to solve their problems. We are a group of highly curious professionals dedicated to discovering and implementing new deep learning models. We work at the intersection of machine learning, statistical analysis, deep learning, natural language processing, and computer vis

ion.We bring out the best in each other, and together, we work towards the vision of using this expertise to help society and make the world a better place.

As a data scientist, you should be passionate about natural language processing, computer vision, statistical sampling, and analytical methods. You will develop machine learning systems, analyze performance, and refine models through hyperparameter tuning and experimentation to optimize

results.

You will also improve algorithm accuracy by iterating based on performance metrics and fee

dback.To succeed in this role, you need exceptional skills in statistics and programming. You will be part of an agile team and will be collaborating with engineers, data engineers, and fellow data scientists.

Job Responsibilities

• Develop and Implement Machine Learning Models: Design, build, and deploy machine learning models and algorithms for various applications, ensuring they are robust and scalable for production use.
• Data Exploration and Preparation: Collect, clean, and preprocess large datasets, including feature engineering and data transformation, to create a strong foundation for modeling.
• Model Training and Optimization: Train models using state-of-the-art techniques, optimize performance through hyperparameter tuning, and conduct thorough experimentation to achieve desired results.
• Analyze and Evaluate Performance: Use appropriate metrics to analyze model accuracy, precision, recall, and other relevant performance indicators, and iteratively improve models based on findings.
• Experimentation and Research: Stay updated on the latest machine learning and data science advancements, and run experiments to identify potential new techniques and approaches for business challenges.

Requirements for the job

• Bachelor’s/Master's/Ph.D. in Computer Science, Mathematics, Statistics, or equivalent field.
• Minimum of 1 to 2 years of experience in ML and AI roles.
• Strong proficiency in Python and machine learning frameworks like PyTorch, TensorFlow, Scikit-learn, and others.
• Solid understanding of statistical analysis, data modeling, and algorithmic techniques for various ML tasks.
• Experience in Natural Language Processing (NLP) and/or Computer Vision (CV) is required; any of the followingis preferred:
• NLP: Strong understanding of RNNs and transformer-based architectures for tasks such as chatbots/dialogue systems, machine translation, named entity recognition, recommendation systems, and retrieval systems.
• Computer Vision: Hands-on experience with cutting-edge Vision Language Models (VLMs) like ViT, CLIP, Swin Transformers, DINO, GroundedSAM, SAM, YOLOv7/v8, and multimodal architectures like BLIP-2 and GIT-2. Skilled in Visual Question Answering (VQA), image classification, search, and object detection, with expertise in advanced techniques for complex vision and multimodal tasks.
• Practical experience in building production-ready systems using deployment frameworks such as FastAPI, NVIDIA Triton Inference Server, TorchServe, or TensorFlow.

SELECTION PROCESS:

1. Interested Candidates are mandatorily required to apply through this listing on Jigya.
2. Only applications received through Jigya will be evaluated further.Shortlisted candidates may be required to appear in an Online Assessment administered by Jigya on behalf on KnowDis
3. Candidates selected after the screening test will be interviewed by Knowdis.ai