Data Scientist
Credit Key- Full Time
- Junior (1 to 2 years)
Candidates should possess at least 5 years of experience in data science or quantitative modeling, ideally within risk or fraud contexts, and hold an advanced degree in a quantitative field such as Mathematics, Statistics, Computer Science, Engineering, or Economics. Strong proficiency in programming languages like Python, R, Spark, and SQL is required, along with the ability to explain complex technical findings to non-technical stakeholders and clients.
As a Data Scientist, you will champion a data-first approach across internal teams and client engagements, building and deploying machine learning models to prevent fraud across diverse fintech use cases, working directly with clients to understand their unique fraud challenges and deliver high-impact, data-driven solutions. You will also evolve risk metrics, the supporting datasets, and how we measure the causal impact of initiatives, collaborate with engineering to scale models into production and optimize performance, and help standardize modeling workflows.
Fraud prevention and compliance platform
Sardine.ai focuses on fraud prevention and compliance for banks, retailers, and fintech companies. Its platform offers tools for risk scoring, transaction monitoring, and customer due diligence, helping clients detect fraud and prevent money laundering. What sets Sardine.ai apart is its ability to monitor customer interactions for fraud signals, using data from over 35 providers to generate accurate risk scores. The company's goal is to enhance security and compliance for financial institutions and retailers.