Chief Data Scientist

Responsabilities

  • Lead data science and machine learning efforts in products and solutions involving IoT, Big Data, Cloud and microservices
  • Come up with innovative machine/deep learning approaches and algorithms that work best for cutting edge problems in AIOps, manufacturing, operations and data centers
  • The products and solutions are being designed using data science, machine learning and deep learning into problems involving predictive analytics, anomaly detection, automated root cause analysis etc. for IT operations, manufacturing and data centers to provide valuable insights and quantifiable RoI to end users
  • Mentor and guide data science team members as well as developers and QA engineers working on the products
  • Work with business/product managers to frame a problem, both mathematically and within the business context
  • Perform exploratory data analysis to gain a deeper understanding of the problem
  • Understand business data and how to use it appropriately in data analysis
  • Construct and fit statistical, machine learning, or optimization models using Spark, TensorFlow and other platforms and frameworks
  • Apply and develop appropriate advanced statistical, machine learning, and/or deep learning models and algorithms to classify structured or unstructured data
  • Collaborate with internal stakeholders to understand business challenges and develop analytical solutions to optimize business processes
  • Test performance of machine learning and deep learning models

Qualifications

  • 10 to 15 years’ overall experience designing, implementing and successfully delivering enterprise/SAAS product with analytics features
  • 5+ years of experience in analytics, data science, data mining, machine learning, deep learning or comparable product/consumer analytics role
  • Bachelor's degree in Computer Science, Operations Research or Math/Statistics
  • Experience in working with multi-dimensional data
  • Top notch communication skills to convey key insights from complex analysis, both oral and written
  • Experience in Spark MLLib, PySpark, NumPy/SciPy, TidyData
    • Experience with agile and Scrum
    • Ability to work with distributed teams in a collaborative and productive manner
  • Experience working with TensorFlow, Open CV, Deep learning experience and time series analysis