Data Analyst
Tailscale- Full Time
- Junior (1 to 2 years)
Candidates should possess 5 years of experience in a data-focused role such as analytics or data science, demonstrating a track record of impactful work, along with strong SQL and Python skills, hands-on experience with BI tools like Tableau, Sigma, or Metabase, and exposure to building ML models. A background in the fraud, risk, or compliance domain is considered a strong plus, and candidates must possess strong communication skills and a pragmatic approach to problem-solving.
The Risk Data Analyst will develop and track key metrics to evaluate risk strategy effectiveness and operational performance, conduct deep-dive analyses to uncover insights for improved decision-making and reduced fraud exposure, build and experiment with ML models to identify fraudulent patterns, partner with engineers to ensure accurate data instrumentation, build and maintain self-serve dashboards and reporting tools, translate business needs into analytical approaches in collaboration with cross-functional teams, and contribute to the design and evaluation of risk mitigation initiatives.
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.