Data Scientist - I

Job Title

Your role:
The Data Scientist is responsible for ensuring data quality, accuracy, and reliability through rigorous validation and cleansing techniques, driving comprehensive quality control measures, working under limited supervision. The role utilizes advanced algorithms and AI, participates in end-to-end data mining projects to extract deep insights from complex data sources. The role deploys and tests data science solutions rigorously, ensuring optimal performance and seamless integration with enterprise systems. The role maintains robust data pipelines and workflows and leverages big data technologies to support advanced analytics projects.

You're the right fit if:

• 10 -15 years experience in AI and Data Science field.

• Master's in computers, electronics, electrical engineering or PhD in relevant streams

• Understanding of the state-of-the-art computer vision, NLP and AI for imaging algorithms

• Experience in developing NLP algorithms, AI based Computer Vision applications

• Experience in NLP techniques for text representation (such as n-grams, bag of words, sentiment analysis etc), semantic extraction techniques, data structures and modeling

• Experience in using GenAI techniques like Agentic frameworks, Auto encoders, Transformers, LLMs, RAG Architecture

• Experience in CV based Deep Learning models like Unet, YOLO etc

• Experience with machine learning and deep learning frameworks, like PyTorch , Tensorflow, OpenCV

• Experience in Deep Learning frameworks like Pytorch, Tensorflow

• Excellent understanding of machine learning techniques and algorithms like k-NN, SVM, Random Forest, privacy models, etc.

• Understanding exploratory data processing techniques such as cleaning and verifying the integrity of data used for analysis

• Experience in generating IP and new ideas/proposals

• Experience in applied statistics skills, such as distributions, statistical testing, regression, etc.

• Experience in building and optimizing reactive and predictive models with Machine Learning techniques

• Experience with one or more analytic software tools or languages like Python, R

• Strong analytical, problem solving and communication skills
  

How we work together
We believe that we are better together than apart. For our office-based teams, this means working in-person at least 3 days per week.

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