Data Scientist, Socure

• Bachelor's Degree in Computer Science, Mathematics, Statistics or similar field of study or equivalent work experience
• Minimum 1-3 years of industry experience working in a similar role
• Demonstrated skills in statistical methods and machine learning to uncover business insights
• Skilled in Python, solid experience working with big data, ideally with a working knowledge of Apache Spark, and Hadoop or similar
• Working experience maintaining and extracting insightful information from Relational Data Base Systems using SQL
• Experience working with AWS, Databricks, and other Big Data tools
• Attitude to thrive in a fun, fast-paced start-up environment with a stellar team of fellow data analysts and programmers
• Excellent problem-solving and analytical skills
• Results-driven individual who does whatever it takes to succeed and loves a challenge
• Effective communicator capable of explaining concepts clearly and credibly across all levels of the organization
• Strong team player, results oriented, metrics driven and capable of working in a fast paced, changing environment

Desirable

• This role offers a unique opportunity to shape the future of Socure’s Consortium Intelligence products by contributing to its cutting-edge, AI-driven solutions. You will work with transaction and account-level data shared by the majority of the top-20 Financial Institutions, Challenger Banks, and Fintechs.
• Your work will focus on uncovering insights through exploratory data analysis, performing data manipulation and quality assessment to ensure consistency and accuracy, and developing algorithms, machine learning models, and advanced analytics to power Socure’s Consortium Intelligence products
• Work in close partnership with product, data scientists, engineers, customers, and other key stakeholders, playing an active role in meetings and discussions with cross-functional teams
• Create and manage large-scale data pipeline jobs, handling complex, high-volume, multi-dimensional data
• Develop machine learning, data mining, statistical, and graph-based algorithms designed to analyze massive data sets, uncovering key insights in fraud and risk patterns
• Collaborate closely with engineering to ensure algorithms are properly implemented and optimized for scale within cloud environments
• Analyze large data sets to develop multiple models and algorithms to detect elusive fraud patterns and identify repeating abusers through a combination of consortium and 3rd party data spanning hundreds of millions of identities and billions of transactions
• Implement new data modeling solutions and improvements to existing solutions
• Integrate new data sources and API-based third-party products into the main modeling framework
• Work with Big Data technologies using Spark
• Provide analytical support to the data science team, collaborate and own your work

• End Date: February 15, 2025