Plume develops and deploys cloud based control planes with scale to manage tens of millions of customer homes through some of the world’s largest Internet Service Providers. Our cloud applications include WiFi network management and optimization, device access control, network provisioning, IoT security, and end customer user interaction through mobile apps.
We are growing our team and looking for talented individuals to help us define and drive the success of our cloud based service offering. Our focus is on the home market and we support B2B and B2C product offerings.
As a Senior Data Scientist you will build solutions to decisions which will directly and largely impact Plume-WIFI's products and millions of its consumers. You will be evaluating, comparing, and applying innovative quantitative research tools and models to answer difficult but critical business questions. Some of the exciting work you’ll do in your first 6-12 months includes building real time, highly scalable, and resilient stream processing ecosystems with Apache Spark, Kafka, Keras, Tensorflow and Redshift/Yugabyte DB. This is a unique ground-floor opportunity for self-motivated individuals to architect, implement and evolve a mission critical state of the art software platform.
What you will do:
- Design and implement critical, highly scalable systems and algorithms to run analytics, workflow and machine learning
- Improve Scalability, Reliability and Performance of our Streaming Data Pipelines built on top of Kafka and Spark
- Help drive the Design and Architecture of next generation Cloud Machine Learning platform
- Design methods to derive Data Insights via efficient and effective feature learning for meaningful problems
Who you are:
- Bachelor’s degree or equivalent in Computer Engineering, Computer Science, Statistics or related field of study plus 5 years of relevant experience in data science.
- Strong ability in Python or Scala and have proficient coding skills
- Proficiency in SQL, ETL scripts
- Experience with Spark, Cassandra or MongoDB and working with large databases/high volume data
- Proficiency in developing algorithms, predictive modeling and concepts of statistics
- Strong Knowledge in machine learning
- Experience with a range of data analysis techniques such as linear regression, random forest, clustering, boosting, Factor analysis, supervised and unsupervised learning, STL analysis, graphic modeling, graph algorithms, etc.
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.