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| Job Location | Bangalore |
| Education | Not Mentioned |
| Salary | Not Disclosed |
| Industry | Banking / Financial Services |
| Functional Area | General / Other Software |
| EmploymentType | Full-time |
The ideal candidate will have a strong knowledge of ML, NLP, Deep Learning, Knowledge Graphs and have experience working with massive amounts of data. They should also have strong software engineering skills and the ability to build systems that reach JP Morgan scale.What Youll Do:5+ years in a growing, and scaling analytics organizations. Excellent demonstrated leadership skills in a global organization.Ability to manage complex relationships across multiple functions and establish strong partnerships. Outstanding communication and presentation skills, written and verbal, to all levels of the organization.Work closely with stakeholders to understand the business imperatives, available data and advise on the problem statement set up for effective ML solutionWork closely with technology leadership for effective management of technology imperatives for Machine Learning life cycle managementDevelop and Train production grade ML/Deep Learning models on large-scale datasets to solve various business usecases for Commercial Banking.Use large scale data processing frameworks such as Spark, AWS EMR, and be proficient at feature engineering across various data sets both structured and un-structured.Use Deep Learning models like CNN, RNN and NLP (state of art Encoder Decoder techniques, LSTMs etc.) for solving various business use casesAbility to build ML models across Public and Private clouds including container-based Kubernetes environments.Work with cross-functional teams to test, implement and deploy models and improve analytical solutions by providing data-driven recommendationsCollaborate with data, design, product and engineering teams to drive effective ML workflows.Basic Qualifications:Advanced Degree in field of Computer Science, Data Science or equivalent engineering disciplineMaster s degree preferredPHD good to have but not necessaryPrimary SkillsetMinimum 8 years of working experience in software industry especially in Data based solution domain with minimum 5+ years into enterprise grade Machine Learning solution build and deployExtensive experience in model development, deployment and online updatesExperience in Business Stakeholder engagement and communication during the a Machine Learning Project executionWell versed in both Theoretical and Practical aspects of Machine Learning.Should have few enterprise grade projects both using Machine Learning and Deep LearningConversant with State of Art NLP techniques i.e. Latest Embedding methods, Transfer Learning and Domain Adaptation methodsShould be comfortable in reading, interpreting and implementing latest Research papers into enterprise spaceConversant in general machine learning techniques i.e. regression, classification, clustering, time series, econometrics, causal inference, mathematical optimizationExpertise with Python, Spark is expectedExpertise in at least one of Tensorflow and PyTorchExperience in cloud based model development platforms like AWS SagemakerModel deployment frameworks i.e. RestFul API, Endpoint creations etc.Advanced SQL skills - comfortable working with very large data sets,
Keyskills :
life cycletime seriesdata sciencedeep learningprivate cloudsdata processingcomputer sciencemachine learningcausal inferencemodel developmentleadership skillssoftware industry