Data Scientist

Requirements
 You have at least 3 to 9 years of industry experience in data mining, machine learning, statistical analysis, and modeling.
 You have an MS or Ph. D. in Computer Science, Physics, Statistics, Applied Mathematics, or any quantitative discipline.
 You have a keen interest in financial services and a passion for shipping high-quality consumer-facing products.
 You are able to self-manage your priorities and deliverables while working in a fast-paced, startup environment.
 You have a solid foundation in computer science and strong competencies in data structures, algorithms, and software design, expertise with statistical data analysis such as linear models, multivariate analysis, stochastic models, and sampling methods.
 You are experienced in one or more of the following areas: Machine Learning (ML) models, ML infrastructure, Natural Language Processing, or Deep Learning.
 You are proficient in one or more data-oriented programming languages/tools (e. g. Python, R. Pandas, Scikit-learn, Jupyter) and database languages (e. g. SQL).
 You have built and prototyped analysis pipelines iteratively to provide insights at scale, on tools such as Hive, Spark, and AWS Redshift.
 You have a spark that separates you from the crowd and the ability to think out of the box and on your feet.
 You possess multi-dimensional skills that make you a valuable co-worker in a fast, changing, and ambiguous environment.
 You have the ability to learn other coding languages as needed really quickly.
 You are comfortable working with a team that deals with ambiguity every day.
 You can articulate complicated technical concepts clearly.
 Demonstrated application of ML techniques in the industry for a problem at scale with fruitful results.
 Ability to build, deploy, and scale ML solutions/platforms including feature store, distributed training, model serving, deployment, experimentation framework, etc.
 Experience using machine learning libraries or platforms such as Tensorflow, Caffe, Theano, Scikit-Learn, Spark ML, etc.
 Hands-on experience with Python, Scala, Go, or Java.
 Knowledge of backend software engineering, data pipelines, and data warehousing technical architectures.
 Knowledge of cloud computing hosted services and multi-tenant cloud infrastructure.

This job was posted by Vaibhav Khare from epiFi,