You are at the right place

Skills & Experience:

Responsibilities:

• Code and build awesome tech in R.
• Create and maintain optimal data pipeline architecture.
• Assemble large, complex data sets that meet functional / non-functional business requirements.
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using R and AWS 'big data' technologies.
• Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
• Keep our data separated and secure through multiple data centers and AWS regions.
• Create data tools for analytics and different team members that assist them in building and optimizing our product into an innovative industry leader.

Skills:

• Bachelor's Degree, Master's Degree, and/or PhD in Statistics, Math, Physics, Computer Engineering or a related field required, or equivalent education.
• Knowledge and interest in leveraging financial data to improve decision-making and generate value.
• Advanced working R knowledge and experience working with data engineering related packages (e.g. purrr, tidyr, dplyr, data.table, tibble).
• Experience with R package development and building production-quality software using R (e.g. plumber APIs, shiny apps)
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement (e.g. profvis, microbenchmark).
• Strong analytic skills related to working with unstructured datasets and bringing it into R (e.g. plyr, jsonlite, readr, ghql).
• Build processes supporting data transformation, data structures, metadata, dependency and workload management.
• Working knowledge of message queuing, stream processing, and highly scalable 'big data' processes (e.g. sparklyr).
• Strong project management and organizational skills (we use Atlassian).
• Experience supporting and working with cross-functional teams in a dynamic environment.
• Experience with relational data stores, SQL and NoSQL databases, including MongoDB (e.g. aws.s3, mongolite)
• Experience with data pipeline and workflow management tools.
• Experience with AWS cloud services: EC2, EMR, RDS, Redshift.
• Experience with containerization and Docker.
• Analytical mind, critical thinker, problem-solver.
• Understanding of the financial services industry and capital markets.