Data Scientist

Interchecks

Interchecks Technologies is a leading venture-backed fintech company dedicated to transforming financial transaction management. We provide payment processing solutions to top operators in online sports betting and fintech.

Founded in 2016 on the simple idea that sending money should be easy, fast, and affordable, Interchecks saw businesses struggling with increasingly complex payments and consumers disappointed with their options. We decided there had to be a better way — so we built it.

Starting with 1099 vendor payments, we expanded rapidly to support real-time payments for gaming operators with the legalization of online gaming in 2018. Unlike many narrow and inflexible payout solutions, Interchecks offers a comprehensive and flexible platform with strong compliance capabilities, enabling us to serve regulated industries like gaming and replicate this success across other fintech verticals.
 

The Opportunity

As a Data Scientist, you will support the development of analytical models that help improve our product quality, risk outcomes, and inform business decisions. Working closely with data scientists, product managers, data engineers and data analysts, you will apply statistical methods and machine learning techniques to analyze data, uncover insights, and contribute to data-driven product improvements.

This role is ideal for someone early in their data science career who is eager to expand their technical skills while gaining experience in a product-focused environment.

Key Responsibilities

• Collaborate with data scientists to develop and improve existing models and analytical processes
• Apply and develop scientific methodology, statistics, and algorithms to identify trends, patterns, and opportunities
• Conduct data exploration to discover and develop predictive features for analytical modeling
• Write efficient SQL queries and work with cloud-based data warehouse to prepare and analyze large-scale data
• Research, design, and implement algorithms to solve complex problems. Demonstrate a deep understanding of key performance metrics to extract valuable insights
• Document workflows, data definitions and processes to support compliance and organizational knowledge sharing

Required Qualifications

• Bachelor’s degree in Statistics, Mathematics, Data Science, or another quantitative field
• 2–4+ years of experience in data science, analytics, or a related quantitative role
• Foundational understanding of statistics, hypothesis testing, regression analysis, and experimental design
• Familiarity with machine learning concepts and common libraries such as scikit-learn
• Proficient with programming in Python
• Proficient in writing SQL queries to extract, transform, and analyze data from diverse data sources
• Strong attention to detail and the ability to work with large datasets while maintaining data integrity
• Excellent analytical and problem-solving skills with the ability to interpret complex data sets and communicate insights effectively

• Exposure to modern warehouses (Snowflake/Redshift)
• Experience utilizing Git/version control
• Strong understanding of data quality principles and best practices