Synechron | Jobs | Associate Data Scientist | BigDataKB.com | 02-02-22

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    Job Location: Bangalore/Bengaluru

    • Minimum 3+ years of working experience as a hands-on data scientist is must
    • Data Science / Data Mining Candidates with expertise in SAS and preferably Banking
    • Programming experience with Python
    • Prior experience with applied statistics, experimental design, machine learning and Gitlab version control is a must
    • Experience with experimenting on different modeling techniques (supervised and unsupervised learning) and develop data visualization for data stories
    • Experience working with Agile methodologies (SCRUM)
    • Able to build and deploy AI models into production with focus on scaling, monitoring and performance
    • A self-starter with high levels of drive, energy, resilience and a desire for professional excellence with a passion for data and data science
    • Lover of math with a strong understanding of statistical methods
    • Solid understanding of statistics, probability, optimisation, ML and DL- Understanding of classical ML techniques (RDF, Boosting, Regression etc), statistical tests, dimensionality reduction techniques.
    • Understanding of Neural networks, CNNs, LSTMs,GRUs and Transformer architectures.
    • Previous experience in at least one domain of computer vision or NLP related problems.
    • Proficiency with any one of pytorch/tensorflow with a history of implementation of some of the above architectures in either of them.
    • Expertise in designing, deploying and maintaining ML model servers in python (both using the sync and async framework).
    • Experience working with any cloud solution (preferably AWS) for hosting and deployment of model servers.
    • Translating business requirements to data science hypotheses and the outcomes back into business impact projections.
    • Able to recognize business needs and ability to communicate with multiple stakeholders including PMs, business owners and operational teams
    • Able to work independently and collaboratively in an interdisciplinary team environment

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