Job Description

The Socure DS Fraud team is responsible for developing cutting edge Fraud, Risk and Synthetic Identification products, building machine learning models using latest ML algorithms and technologies, building data-processing pipelines, evaluating the performance of new data sources, and providing analytical support to the Socure Fraud and Risk product suite.

In this role you will:

Develop machine learning, data mining, statistical, and graph-based algorithms designed to analyze massive data sets; partner with Cloud technologists to ensure proper implementation and usage of said algorithms
Analyze large data sets to develop multiple, custom models and algorithms to drive innovative correlations for fraud and acceptance data as well as social data
Implement new data modeling solutions and improvements to existing solutions
Integrate new data sources and API third-party products in the main framework
Work with Big Data technologies using Spark
Provide analytical support to the data science team
Own and drive projects from conception to completion
Collaborate with data scientists, engineers and other key stakeholders
Work well in a fast-paced cross-functional environment

Requirements:

BE/B.TECH/ME/MSc in computer science, mathematics, physics, statistics or similar or equivalent work experience
A minimum of 5+ years of industry experience working in a similar role
Experience in developing data-driven algorithms in information retrieval, relevance, or machine learning and working with distributed systems
Strong Python, R, Bash/Shell programming background
Good working knowledge of SQL

Nice to have:

Dashboard development experience (Dash, Bokeh, R Shiny)
Experience with data workflow managers such as Airflow, Drake, or Luigi
Experience in advanced analytics and developing machine learning models
Programming experience in Scala, Java
Experience in Hadoop, Spark, distributed systems
Experience with containerization (Docker)
Experience with cloud ecosystems such as Microsoft Azure, Google Cloud Platform or Amazon Web Services

Valid through: 4/24/2021