Data Scientist Code DS:101

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???????????????? ???????????? ????????????????????????????????????????????????????????????????: • Research and develop statistical learning models for data analysis • Collaborate with product management and engineering departments to understand company needs and devise possible solutions • Keep up-to-date with latest technology trends • Communicate results and ideas to key decision makers • Implement new statistical or other mathematical methodologies as needed for specific models or analysis • Optimize joint development efforts through appropriate database use and project design. • Selecting features, building and optimizing classifiers using machine learning techniques • Data mining using state-of-the-art methods • Extending company’s data with third party sources of information when needed • Enhancing data collection procedures to include information that is relevant for building analytic systems • Processing, cleansing, and verifying the integrity of data used for analysis • Doing ad-hoc analysis and presenting results in a clear manner • Creating automated anomaly detection systems and constant tracking of its performance • Perform other related duties and responsibilities associated with the position. ???????????????? ???????????????? ???????????????? ???????????? ???????????? ???????????????? ????????????????? • Bachelors or Masters in Computer Science/Engineering, Statistics, Mathematics from a recognized university. • 5-8 years of relevant working experience. • Highly analytical thinking with demonstrated talent for identifying, scrutinizing, improving, and streamlining complex work processes. • Exceptional listener and communicator who effectively conveys information verbally and in writing. • A can do attitude with able to learn new technologies on the go. • Resourceful team player who excels at building trusting relationships with customers and colleagues. • Flexible team player who thrives in environments requiring ability to effectively prioritize and juggle multiple concurrent projects. • Proven ability to develop quality standards, testing procedures, inspection reporting formats, and ability to conceptualize tasks and accomplish them. • Good knowledge of Algorithm optimization and Data-Structures. • Experience in programming languages such as Python, C++, and Scala. • Knowledge of Different cloud vendors GCP, AWS. • Able to build Production machine learning pipelines and write production code. • Able to deploy machine learning and deep-learning models using Dockers, Kubernetes and server-less computing. • Able to understand basic Applied Math and Bayesian-Statistics • Machine learning, Deep Learning algorithm (Classification, clustering, association rules etc.) and their applications. • Strong understanding of NoSQL Databases. • Knowledge visualization tools like D3js, ggplot, HighCharts. • Knowledge of web-frameworks like VueJS. • State of the art machine learning & deep learning tools. • Knowledge of frameworks like Flask, Django. • Apache Spark, Sklearn, keras, Pytorch. • Open-Source Contributor.