Role – AIML Data Scientist
Location : AIA Group - Bhubaneswar
Exp : 5 to 12 years
Job Description
- Be a hands on problem solver with consultative approach, who can apply Machine Learning & Deep Learning algorithms to solve business challenges
- Use the knowledge of wide variety of AI / ML techniques and algorithms to find what combinations of these techniques can best solve the problem
- Improve Model accuracy to deliver greater business impact
- Estimate business impact due to deployment of model
- Work with the domain / customer teams to understand business context , data dictionaries and apply relevant Deep Learning solution for the given business challenge
- Working with tools and scripts for sufficiently pre-processing the data & feature engineering for model development – Python / R / SQL / Cloud data pipelines
4. Design , develop & deploy Deep learning models using Tensorflow / Pytorch
Experience in using Deep learning models with text, speech, image and video dataDesign & Develop NLP models for Text Classification, Custom Entity Recognition, Relationship extraction, Text Summarization, Topic Modeling, Reasoning over Knowledge Graphs, Semantic Search using NLP tools like Spacy and opensource Tensorflow, Pytorch, etcDesign and develop Image recognition & video analysis models using Deep learning algorithms and open source tools like OpenCVKnowledge of State of the art Deep learning algorithmsOptimize and tune Deep Learnings model for best possible accuracyUse visualization tools / modules to be able to explore and analyze outcomes & for Model validation eg : using Power BI / TableauWork with application teams, in deploying models on cloud as a service or on-premDeployment of models in Test / Control framework for trackingBuild CI / CD pipelines for ML model deploymentIntegrating AI&ML models with other applications using REST APIs and other connector technologiesConstantly upskill and update with the latest techniques and best practices. Write white papers and create demonstrable assets to summarize the AIML work and its impact.Technology / Subject Matter ExpertiseSufficient expertise in machine learning, mathematical and statistical sciencesUse of versioning & Collaborative tools like Git / GithubGood understanding of landscape of AI solutions – cloud, GPU based compute, data security and privacy, API gateways, microservices based architecture, big data ingestion, storage and processing, CUDA ProgrammingDevelop prototype level ideas into a solution that can scale to industrial grade strengthAbility to quantify & estimate the impact of ML modelsSoftskills ProfileCuriosity to think in fresh and unique ways with the intent of breaking new ground.Must have the ability to share, explain and 'sell' their thoughts, processes, ideas and opinions, even outside their own span of controlAbility to think ahead, and anticipate the needs for solving the problem will be importantAbility to communicate key messages effectively, and articulate strong opinions in large forumsDesirable Experience :Keen contributor to open source communities, and communities like KaggleAbility to process Huge amount of Data using Pyspark / HadoopDevelopment & Application of Reinforcement LearningKnowledge of Optimization / Genetic AlgorithmsOperationalizing Deep learning model for a customer and understanding nuances of scaling such models in real scenariosOptimize and tune deep learning model for best possible accuracyUnderstanding of stream data processing, RPA, edge computing, AR / VR etcAppreciation of digital ethics, data privacy will be importantExperience of working with AI & Cognitive services platforms like Azure ML, IBM Watson, AWS Sagemaker, Google Cloud will all be a big plusExperience in platforms like Data robot, Cognitive scale, H2O.AI etc will all be a big plusSkills Required
Machine Learning, Tableau, Ibm Watson, Tensorflow, Nlp, Python, Pyspark, Github, Hadoop, Power Bi, reinforcement learning, Sql, Google Cloud, Deep Learning, Azure ML, Git, Opencv, Pytorch, genetic algorithms