Guavus, Inc. is seeking a Senior Scientist to join our analytics team. The successful candidate will join a team of scientists and engineers creating new, complex machine learning and artificial intelligence algorithms and proving them with our customers. 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 our San Jose CA, USA office.
A Senior Scientist at Guavus is responsible for transforming a novel idea into a precise technical problem/hypothesis and leading the design and execution of a machine learning/artificial intelligence solution, validating it through one or more POCs in concert with customers. This includes creating and implementing the algorithms in Python/Java/Scala, designing the measurements and tests, and proving that the analytics solves the technical problem. In addition to the analytics team, our senior scientists work closely with our product management, engineering and field teams and represent the company in analytics discussions with customers, partners and at conferences.
The ideal candidate must have demonstrated an ability to independently create novel, mathematically sound algorithms, develop and test research code suitable for POCs demonstrating proof of value.
Roles & Responsibilities:
- Creating mathematically based algorithms for use in the predictive and prescriptive, streaming analytics of high volume and high-velocity data, including identifying state of the art techniques.
- Implementing predictive and/or prescriptive analytics pipelines in Python/Java /Scala.
- Quickly designing and conducting tests with the associated data to demonstrate a proof of value.
- Documenting algorithms, model building, data analysis and results.
- Communication of results to colleagues, customers, and partners.
- Owning the algorithms in machine learning/artificial intelligence modules in our product lines.
- Must be self-driven and capable of prioritizing, organizing, and managing a substantial workload as well as supervising the work of others.
- Work effectively in a globally distributed team.
- PhD in an engineering or science field
- A minimum of 5 years, post PhD, of experience in solving significant problems involving the analysis of terabytes of structured and/or unstructured data.
- Prior experience in at least one of operations analytics, marketing analytics, security analytics, NLP and/or complex data mining/analysis projects.
- Prior research demonstrating a solid mathematical background (statistics, linear algebra, PDEs, etc.) and/or heavy emphasis on data analysis including data mining/machine learning/artificial intelligence.
- Algorithmic understanding of classic machine learning methods (e.g., Random Forest, Stochastic Gradient Descent).
- In-depth experience using analytics enabling packages such as scikit-learn, spark ml/mllib, scipy, numpy, pandas, spark.
- Expert knowledge of SQL and at least one of Java, Scala or Python.
- Self-driven with the ability to collaborate as a respected domain expert in a multidisciplinary technical team.
- Excellent oral and written communication skills, including the ability to present effectively to both business and technical audiences.
- Prior experience with neural networks (e.g. LSTM), reinforcement learning, manifold learning, etc.
- Advanced mathematical background: topology, differential geometry, group theory, etc.
- Knowledge of Hadoop and Spark.
- At minimum, a basic understanding of communications networks and IT systems.