Job
Description
As an AIML Data Scientist, you will be a hands-on problem solver with a consultative approach, applying Machine Learning & Deep Learning algorithms to solve business challenges. You will utilize a wide variety of AI/ML techniques and algorithms to determine the best combinations for problem-solving. Your responsibilities will include estimating the business impact of deploying models, understanding business context and data dictionaries, and implementing relevant Deep Learning solutions for specific business challenges. You will also be involved in pre-processing data, feature engineering, and model development using tools such as Python, R, SQL, and Cloud data pipelines. Key Responsibilities: - Use Deep learning models for text, speech, image, and video data - Design and develop Image recognition & video analysis models with Deep learning algorithms and tools like OpenCV - Utilize visualization tools/modules for exploring, analyzing outcomes, and Model validation using tools like Power BI / Tableau - Collaborate with application teams to deploy models on cloud or on-premises - Deploy models in Test/Control framework for tracking - Build CI/CD pipelines for ML model deployment - Integrate AI&ML models with other applications using REST APIs and connector technologies - Write white papers and create demonstrable assets summarizing AIML work and its impact - Utilize expertise in machine learning, mathematical and statistical sciences - Understand the landscape of AI solutions including cloud, GPU-based compute, data security, privacy, API gateways, microservices architecture, big data processing, and CUDA Programming - Quantify and estimate the impact of ML models Qualifications Required: - 4 to 13 years of experience in AIML Data Science - At least 2+ years of relevant experience - Experience with tools such as Python, R, SQL, Cloud data pipelines - Understanding of Deep Learning algorithms and techniques - Familiarity with visualization tools like Power BI / Tableau - Experience in deploying models on cloud or on-premises - Knowledge of CI/CD pipelines for ML model deployment - Proficiency in integrating AI&ML models with other applications using REST APIs - Strong communication skills and the ability to work collaboratively in a team environment Desirable Experience: - Active contribution to open-source communities and platforms like Kaggle - Ability to process large amounts of data using Pyspark/Hadoop - Understanding of stream data processing, RPA, edge computing, AR/VR, etc. - Appreciation of digital ethics and data privacy - Experience with AI & Cognitive services platforms like Azure ML, IBM Watson, AWS Sagemaker, Google Cloud - Familiarity with platforms like DataRobot, CognitiveScale, H2O.AI, etc. As an AIML Data Scientist, you will be a hands-on problem solver with a consultative approach, applying Machine Learning & Deep Learning algorithms to solve business challenges. You will utilize a wide variety of AI/ML techniques and algorithms to determine the best combinations for problem-solving. Your responsibilities will include estimating the business impact of deploying models, understanding business context and data dictionaries, and implementing relevant Deep Learning solutions for specific business challenges. You will also be involved in pre-processing data, feature engineering, and model development using tools such as Python, R, SQL, and Cloud data pipelines. Key Responsibilities: - Use Deep learning models for text, speech, image, and video data - Design and develop Image recognition & video analysis models with Deep learning algorithms and tools like OpenCV - Utilize visualization tools/modules for exploring, analyzing outcomes, and Model validation using tools like Power BI / Tableau - Collaborate with application teams to deploy models on cloud or on-premises - Deploy models in Test/Control framework for tracking - Build CI/CD pipelines for ML model deployment - Integrate AI&ML models with other applications using REST APIs and connector technologies - Write white papers and create demonstrable assets summarizing AIML work and its impact - Utilize expertise in machine learning, mathematical and statistical sciences - Understand the landscape of AI solutions including cloud, GPU-based compute, data security, privacy, API gateways, microservices architecture, big data processing, and CUDA Programming - Quantify and estimate the impact of ML models Qualifications Required: - 4 to 13 years of experience in AIML Data Science - At least 2+ years of relevant experience - Experience with tools such as Python, R, SQL, Cloud data pipelines - Understanding of Deep Learning algorithms and techniques - Familiarity with visualization tools like Power BI / Tableau - Experience in deploying models on cloud or on-premises - Knowledge of CI/CD pipelines for ML model deployment - Proficiency in integrating AI&ML models with other applications using REST APIs - Strong communication skills and the ability
