SEW Engineering | Data Scientist || Walk-In || 5th-6th Jan | Hybrid – Noida(Sector-62 Noida) | Bharat | | 2023-02-24

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Job Location: Hybrid – Noida(Sector-62 Noida)

Job Detail:

Roles and Responsibilities

• Masters degree in Machine Learning, Data Science, Computer Science, Mathematics, Statistics, or related engineering field or a bachelors degree with a significant amount of relevant work experience. Jyotish Jyotish - Career & Life Prediction
  • Retrieving and analyzing data using SQL/Python from SQL or NoSQL database such as SSMS, Postgres, MongoDB, Cassandra, etc.
  • Hands-on knowledge of data modelling tools, data mapping tools, and data profiling tools.
  • Experience with and theoretical understanding of algorithms for supervised and unsupervised modeling such as classification, regression, clustering, recommendation engine and anomaly detection
  • Experience in Python programming and familiarity with python libraries such as numpy, pandas, scikit-learn etc.
  • Leverage advanced NLP algorithms/architectures to build custom models for entity extraction and concept recognition, relation extraction, summarization, textual classification and clustering, etc.
  • Contribute to the execution of our vision for NLP-based technology solutions using various NLP toolkits like Spacy, CoreNLP, OpenNLP, etc.
  • Perform relevant data analysis and benchmark the NLP solutions to improve our offerings.
  • Expertise with statistical data analysis. (e.g. linear models, multivariate analysis, stochastic models, sampling methods, A/B testing)
  • Experience in deploying machine learning products in production using docker is a plus.
  • Experience supporting and working with cross-functional teams in a dynamic environment.
  • Experience with object-oriented/object function scripting languages: Python preferable.
  • Strong in BI technologies: e.g. Microsoft Power BI (preferable), Tableau, Google Analytics.
  • Experience building and optimizing big data’ data pipelines, architectures and data sets, Azure Cloud experience preferred

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