Baker Hughes | Hiring | Senior Staff Data Scientist | BigDataKB.com | 07-04-2022

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Job Location: Mumbai

  • As a Data Scientist, you would be working with subject matter experts in energy production.
  • You will help in building models on reliability, predictive analysis, production optimizations and other interesting industry problems.

As a Staff Data Scientist, you will be responsible for:

  • Contributing in development and deployment of applied, predictive and prescriptive analytics. Develop self-learning systems that can predict failures and autocorrect based on data
  • Gathering & analyzing data, devising data science solutions for high-performance models in scalable code. Propose innovative algorithms and pursue patents where appropriate.
  • Working with engineering teams to incorporate solutions and create intuitive UX stories. Partner with data engineers on data quality assessment, cleansing and analytics.
  • Researching and evaluating emerging technology and market trends to assist in project development and operational support for multiple teams or complex scenarios.
  • Contributing to the development of software and data delivery platforms that are service-oriented with reusable components across multiple teams.
  • Creating reports and other artifacts to document your work and outcomes. Communicating methods, findings, and hypotheses with stakeholders.

To be successful in this role you will:

  • Have a MS Degree in Computer Science or in STEM, Majors.
  • 6+ years as data scientist and technical hands-on coding experience.
  • Have experience in Machine Learning/AI techniques including Deep learning (RNN, CNN, GAN, etc), Support Vector Machines; Regularization Techniques; Boosting, Random Forests, Ensemble Methods, image/video/audio processing, Bayesian and time series modelling.
  • Have experience in Parallel programming frameworks for GPUs, TPUs and developed containerized solutions (Docker/Mesos etc).
  • Have good implementation experience with R, Python, Perl, Ruby, Scala, Apache Spark, Storm, SAS and ability to work with a variety of Deep learning frameworks including TensorFlow, Keras, Caffe, CNTK, etc
  • Have hands-on skills in sourcing, manipulating and analyzing large volumes of data including SQL and NoSQL databases
  • Have proven experience in using well-established supervised and unsupervised machine learning methods for large industry-strength data analysis problems.
  • Reviews, analyses and develops architectural requirements at domain level, aligning architectural requirements with software development strategy.
  • Leads and facilitates the domains architecture governance process based on EAs governance structure.

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