Responsibilities:
· Providing technical leadership to deliver and productionize models for a team of data scientists and ML engineers or contribute independently
· Consult with business stakeholders across geographical locations regarding algorithm-based recommendations and be a thought-leader to develop these into business actions.
· Mentor peers and junior members and handle multiple projects at the same time.
· Manage the continuous improvement of data science and machine learning led initiatives by following industry best practices and staying up to date with and extending the state-of-the-art in data science research.
· Excellent academic or industrial track record of proposing, conducting and reporting results of original research, plus collaborative research with publications.
· Participate and speak at various internal and external forums such as ML / AI conferences.
Qualifications:
· Must have 8 to 11 years of overall IT experience
· Must have 5+ years of hands on Model building
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Responsibilities:
· Providing technical leadership to deliver and productionize models for a team of data scientists and ML engineers or contribute independently
· Consult with business stakeholders across geographical locations regarding algorithm-based recommendations and be a thought-leader to develop these into business actions.
· Mentor peers and junior members and handle multiple projects at the same time.
· Manage the continuous improvement of data science and machine learning led initiatives by following industry best practices and staying up to date with and extending the state-of-the-art in data science research.
· Excellent academic or industrial track record of proposing, conducting and reporting results of original research, plus collaborative research with publications.
· Participate and speak at various internal and external forums such as ML / AI conferences.
Qualifications:
· Must have 8 to 11 years of overall IT experience
· Must have 5+ years of hands on Model building experience using Machine Learning, Deep Learning and NLP
· Experience in Designing and implementing ML pipelines and systems to train and deploy ML algorithms in a scalable, reliable, and cost-effective manner
· Authoritative experience in the field of Data Science to influence stake holders across varied work streams and geographical locations, ability to challenge the status quo to improve the base line models and the models which are already productionized.
· Experience in machine learning, supervised and unsupervised: Forecasting, Classification, Data/Text Mining, NLP, Decision Trees, Adaptive Decision Algorithms, Random Forest, Search Algorithms, Neural Networks, Deep Learning Algorithms.
· Strong implementation experience with Python with best practices, and familiarity with Linux/Unix/Shell environments
· Strong hands-on skills in sourcing, cleaning, manipulating and analyzing large volumes of data using distributed computing platform
· Worked with at least one mainstream machine learning frameworks, including caffe, convNet, Tensor Flow, Torch
· Experience working with modern tools for big data processing and scalable machine learning (e.g., AWS, GCP, Kafka, Apache Spark, Hadoop, SQL, NoSQL), Kubernetes and dockers
· Deep understanding of the latest data science and data engineering methods and processes to develop impactful and reusable patterns and abstractions from enterprise-level data assets
· Experience in using code versioning tools like GIT, bit bucket; DevOps experience building CI/CD pipelines for ML projects
· Good to have experience in training ML models in tools like Sage Maker, Kubeflow etc.
· Good to have experience in frameworks to depict interpretability of models using libraries like Lime, Shap etc.
· Good to have experience with any of the cloud platforms – AWS/GCP/Azure
· Superior verbal, visual and written communication skills to educate and work with cross functional teams on controlled experiments.
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