Numentica LLC
Location
Coimbatore | India
Job description
This is a remote position.
Position Summary:
As a lead engineer responsible to engineer efficient adaptable and scalable data pipelines to process structured and unstructured data for cloudbased machine learning applications that enhance our Constituent experience will have a unique opportunity to use your quantitative skills in statistics machine learning to answer high impact open questions prototype cutting edge algorithms engage in large scale experimentation and drive business insights through data Understand companys data strategy business priorities and success measures to provide context for designing and building models. Essential Functions/Responsibility: Designing machine learning pipelines that curate datasets train test and validate models compare model performance to existing or previously cataloged models and then package the models and either deploy them to a realtime serving layer or handle batch scoring activities Conduct data profiling cataloging and data mapping for technical design using a use casebased approach that drives the construction of technical data flows. Assess the effectiveness and accuracy of data sources and data gathering techniques Design and develop Machine Learning and Statistical Models (preferably using R & Python) and other data analysis techniques to collect explore and extract insights from structured and unstructured data Collaborate with Microsoft Cloud Solution Architects and Data Platform Engineers in developing complex endtoend Enterprise solutions on Microsoft Azure platform.
Minimum Qualifications
Bachelor s degree or MS degree in Computer Science Informatics Statistics Applied Mathematics Data Science Machine Learning or equivalent. Ph. D. preferred. Should have extensive experience with NLP data processing flant5 finetuning peftlora and Azure ML are mandatory. At least 7 years handson experience with data science AI and big data. Experience with data engineering. Experience with one or more Data Science/Machine Learning tools and frameworks (i.e. Python Scikit NLTK NumPy PyMongo Pandas TensorFlow R Spark) Machine learning using kNN naive bayes decision trees SVM experience required Knowledge and experience with Model Management ideally using Azure ML service and/or MLFlow as well as deployment of models using Azure Kubernetes Service Deep understanding of statistical and machine learning modeling with experience applying these modeling techniques to business problems. Experience using data mining and statistical tools. Solid pattern recognition and predictive modeling skills. Knowledge of recommendation engines scoring systems A/B testing. Experience leveraging a variety of services to act as data sources such as Azure Data Lake Azure Synapse Analytics Azure SQL Azure EventHub/IoT Hub etc. Knowledge of using automated machine learning (AutoML) frameworks to enhance productivity Extensive experience connecting to Data Platforms including data lakes data warehouses NoSQL databases and APIs. Ability to set up data and experimental platforms Knowledge of data query and data processing tools (T SQL) Communication is essential for this role must be able to listen and understand the question and develop and deliver clear insights. Outstanding team player. Azure Certifications (DP100 would be a HUGE Plus)
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