Data Scientist

Job Description 
What will a 'Data Scientist - Data Analytics' do?
  • Providing a full range of Data and Analytic services(ML, Data Mining, EDA, Feature Engineering, Statistical modeling for Predictive and Prescriptive enterprise analytics) to clients across multiple sectors.
  • Applicants will be expected to work with a diverse set of data sources, such as time series data, spatial, graph data, semi-structured and unstructured data, and build statistical/machine-learning models in support of on-demand, real-time analytic services.
  • Assess the effectiveness and accuracy of new data sources and data gathering techniques.
  • Develop custom data models and algorithms to apply to data sets.
  • Use predictive modeling to increase and optimize customer experiences, revenue generation and many other business outcomes.
  • Develop company A / B testing framework and test model quality.
  • Develop processes and tools to monitor and analyze model performance and data accuracy.
  • Work with partners in Data Engineering, Product, Programmatic and business teams, to operationalize integration of analytic models into the production environment(s).
  • Stay current on relevant academic and industry developments to identify best-in-class algorithms, techniques, libraries, etc.

What we are looking for?

  • Business-minded data scientist with a demonstrated ability to deliver valuable insights via data analytics and advanced data-driven methods.
  • Developed intricate algorithms based on deep-dive statistical analysis and predictive data modeling.
  • Experience using statistical computer languages like R, SAS, Python etc.. to manipulate data and draw insights from large data sets.
  • Analyze and process complex data sets using advanced querying, visualization andanalytics tools.
  • Passion for solving unstructured and non-standard mathematical and behavioral problems
  • End-to-end experience with data, including querying, aggregation, analysis, and visualization.
  • Experience implementing Machine Learning and Deep Learning Algorithms, Data-Driven Personalization.
  • Excellent communication and presentation skills, being able to explain complex problems and the solutions applied.
  • Demonstrating data analysis and visualization with one or more leading COTS analytic and presentation solutions including Tableau, Power BI, Qlik view or Qlik Sense, and MS Excel and other MS Office suite applications.
  • Experience in an Agile environment (SAFe) and work within the Atlassian suite (Jira, Bitbucket, Confluence) and AWS or other computing environments.
Tools: R, Python, Spark, PySpark, Scala, Tensorflow, Keras, Big Data, AWS

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