Data Scientist

Job Description :

Senior Data Scientist – Cognitive Services and AI / ML

Experience Level : 6-12 years Competency : Cognitive Services

Chennai-WFO‎

Primary Skill :

Artificial Intelligence & Machine Learning (AI / ML) Algorithms

Secondary Skill :

Natural Language Processing (NLP)

Computer Vision

Cloud-based AI Services (AWS SageMaker, Azure Cognitive Services, Google AI Platform)

Job Description (JD) :

The Data Scientist specializing in Cognitive Services will develop and deploy AI / ML solutions that leverage advanced algorithms to solve complex business problems. The role focuses on integrating machine learning models into applications powered by cognitive capabilities such as image recognition, speech-to-text, and sentiment analysis. . .

Roles and Responsibilities :

AI / ML Model Development : Design and implement machine learning models tailored for cognitive services.

Algorithm Design : Leverage algorithms for regression, classification, clustering, NLP, and computer vision tasks.

Data Integration : Collaborate with data engineers to ensure high-quality and well-structured data pipelines.

Cloud Services : Utilize AI / ML tools on platforms like AWS, Azure, or Google for training, deployment, and scalability.

Model Deployment : Work with MLOps frameworks to deploy and monitor models in production environments.

Cross-functional Collaboration : Partner with software developers and business analysts to integrate cognitive services into customer-facing applications.

Performance Optimization : Optimize models and algorithms for speed and scalability.

Research & Innovation : Stay abreast of emerging AI / ML technologies and incorporate them into cognitive solutions.

Qualifications :

Master’s or PhD in Data Science, Machine Learning, or a related field.

8+ years of hands-on experience in AI / ML with a focus on cognitive services.

Proficiency in frameworks such as TensorFlow, Py Torch, and Scikit-learn.

Expertise in Python, R, and SQL.

Experience with cloud-based AI tools and services like AWS Sage Maker or Azure Cognitive Services.

Strong understanding of ML Ops practices.

Preferred Skills :

Familiarity with neural networks for advanced deep learning tasks.

Knowledge of speech recognition, image processing, and sentiment analysis technologies.

Experience with big data tools such as Apache Spark and Hadoop.

Certification in AWS, Azure, or Google Cloud AI services.