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Senior Director of Analytics

Gurgaon, India

Guavus, a Thales Company, is seeking a Senior Director of Analytics to join our company delivering Artificial Intelligence innovations in the communications service provider and IOT spaces. The successful candidate will direct all Analytics activities in our offices in India including leading teams creating & validating new, complex machine learning and artificial intelligence algorithms. This is an exciting, highly technical role that is focused on enabling customers to create business value through advanced, real-time analytics on their streaming big data, both structured and unstructured. This full-time position is based in Gurgaon, India. Interested applicants suited to the description below are urged to submit their resumes/CVs to

As a Sr. Director of Analytics at Guavus you will be responsible for driving research agendas including (a) transforming a vision for analytics into precise technical problems/hypotheses, (b) leading the design and execution of machine learning/artificial intelligence solutions, (c) the execution of PoCs/PoVs with customers and (d) supporting our Engineering, Product and Field organizations in the commercialization of our analytics. This position has visibility at a cross-company level including regular interactions with the senior executive staff of the company and representing Guavus’ analytics in discussions with customers, partners and at conferences.

Roles & Responsibilities:

  • Be the cross-organizational steward of Analytics practices in Guavus India
  • Contribute, at the highest levels, to the analytics strategy of the company
  • Direct a staff of senior team members in the creation and application of algorithms for use in the predictive and prescriptive analytics of high volume and high velocity data
  • Provide deep technical guidance to our scientists in the development of novel ML and AI algorithms
  • Communicate our analytics strategy and tactics to colleagues, customers, and partners
  • Mentor team members and represent their needs and interests to executive management
  • Work effectively in a globally distributed team

Required Background:

  • An advanced degree in an Engineering or Science field, Ph.D. preferred.
  • A minimum of 15 years, of experience in solving significant problems involving the analysis of terabytes of structured and/or unstructured data, leading to the creation of commercial offers
  • Led the creation of machine learning and/or artificial intelligence algorithms with proven commercial value in at least one of Operations Analytics, Marketing Analytics, and IOT Analytics
  • Prior research evidencing a solid mathematical background (Statistics, Linear Algebra, PDEs, etc.) and/or heavy emphasis on data analysis including data mining/machine learning/artificial intelligence
  • Led customer engagements on analytics projects
  • Demonstrated ability to translate technical results into business value propositions
  • Demonstrated ability to lead teams of scientists/engineers in a dynamic environment
  • Experience collaborating with other teams in a software company – especially Engineering, CTO, Product Management, Sales, Marketing and Customer Success
  • Algorithmic understanding of classic machine learning methods (e.g., Random Forest, Stochastic Gradient Descent) as well as deep learning (e.g., CNN, LSTM)
  • In depth experience using analytics enabling packages such as scikit-learn, spark ml/mllib, scipy, numpy, pandas, spark
  • Proven ability to architect analytics pipelines and design components for platforms
  • Expert knowledge of SQL, Python and at least one of Java/Scala
  • Excellent oral and written communication skills, including the ability to present effectively to both business and technical audiences
  • Must be self-driven and capable of prioritizing, organizing, and managing a substantial workload

Desired Background:

  • Expertise with Reinforcement Learning, Manifold Learning, NLP, etc.
  • Experience in software development
  • Knowledge of Hadoop and Spark
  • At least a basic understanding of communications networks and IT systems