04 Nov
Lead Data Scientist - ML Ops
Oregon, Portland , 97201 Portland USA

About GSPANNWe work in an exploding market of retail and e-commerce. We have served as a trusted business partner for some of the world’s most respected brands. We’ve worked with more than 200 organizations and have served as a trusted business partner for some of the world’s most respected brands. Our solutions have the businesses create custom-designed technology platforms, which have transformed the way our clients connect with their employees, partners, and customers. GSPANN is headquartered in Milpitas, CA with satellite offices around the world.To know more about GSPANN, visit our website www.gspann.com Or connect on social media platforms: LinkedIn, Twitter and Facebook.

Location: Portland, OR (Remote till covid Control)

Duration: Long Term
  • Data Scientist with experience in developing and deploying Image recognition models
  • Advanced Degree in Mathematics, Physics, Computer Science, Engineering, Statistics, or an equivalent discipline required
  • Experience in developing models and algorithms in a commercial environment with a track record of creating meaningful business impact
  • Experience in

    developing ML Ops pipelines
  • Experience with SQL and Python skills required; proficiency in at least one open-source programming language (R, Java, C or another) desirable
  • Strong on

    data analysis and visualization.
  • Expertise in multivariate statistical modelling (e.g. clustering, regression, principal components and factor analysis, time-series forecasting, Bayesian methods) and machine learning (Random Forest, KNN, SVM, boosting and bagging, regularization etc.) required
  • Expertise in presenting model performance insights using visualization software (Plotly preferred)
  • Experience with cloud computing platforms (Azure, Google Cloud Platform or AWS), or equivalent on-premise platform
  • Ability to simultaneously coordinate and track multiple deliverables, tasks and dependencies across multiple stakeholders / business areas.
  • Experience with neural networks and deep learning, using frameworks such as TensorFlow, desirable

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