At Entropik Technologies, we build systems that measure and analyzes human emotions at an unprecedented scale, with accuracy, speed, and mission-critical availability.
We work with some of the leading brands and agencies across the globe who utilizes our platform to improve overall customer experience, understand consumer behavior and their subconscious responses.
The Data Science team at Entropik is a high profile team that is a center of innovation for the company and a major contributor to the company's core products.
The types of challenges we solve have attracted people from industry and academia with diverse backgrounds.
We're passionate about maintaining an open and collaborative environment, where team members bring their own unique style of thinking and tools to the table.
Responsibilities : Work on challenging fundamental data science problems in affective computingPropose and develop solutions independently and work with other data scientistsDrive the collection of new data and the refinement of existing data sourcesContinuous focus on enhancing the current models with an overall goal of improving the accuracy of different emotion touch pointsPrepare white papers, scientific publications and conference presentationsWork closely with product and engineering teams to identify and answer important product questionsCommunicate findings to product managers and engineerAnalyze and interpret the resultsDevelop best practices for instrumentation and experimentation and communicate those to product engineering teamsRequirements : Masters or Ph.D.
in a relevant technical (deep learning, machine learning, computer science, physics, mathematics, statistics, or related field), or 4+ years' experience in a relevant roleExtensive experience solving analytical problems using quantitative approaches using machine learning methodsShould be experienced in Computer Vision and Visual Feature Extraction.
Experienced with Deep Learning Libraries like Tensorflow, Pytorch and architectures like CNN, RCNN.Track record of using advanced statistical methods, information retrieval, data mining techniquesComfort manipulating and analyzing complex, high-volume, high-dimensional data from varying sourcesA strong passion for empirical research and for answering hard questions with dataA flexible analytic approach that allows for results at varying levels of precisionFluency with at least one scripting language such as PythonExperience with at least some of the following machine learning libraries : scikit-learn, H2O, SparkML, etcExperience with practical data science : source control workflows, deploying machine learning models in production, real-time machine learning.
Skills : - Data Science, Python, Machine Learning (ML) and Deep Learning