Softeta is a software engineering partner for finance, energy, industrial, and other high-stakes sectors. We specialize in building and modernizing backend-heavy, integration-critical systems where speed, accuracy, and reliability are non-negotiable. With 100+ AI and custom software experts across engineering hubs in Lithuania and Poland, we embed ourselves directly into client operations — delivering custom software, automation, and AI where they drive the most value. Clients such as SEB, NordVPN, and CarVertical trust us with systems that serve millions of users globally. We strive for excellence, that’s why we created Cobble – Softeta’s own AI-native development workflow, built by our engineers, that standardizes how developers work with AI agents from requirement to working code.

We’re looking for an experienced Analytics Engineer to take ownership of fraud analytics, forensic investigations, and attack pattern detection. The role will provide immediate analytical support, independently handle fraud investigations, and reduce the workload of backend engineering teams.

Job description:

• Investigate fraudulent activities and suspicious transactions.
• Identify and analyze fraud patterns, attack methods, and anomalies.
• Perform data-driven forensic investigations and root cause analysis.
• Analyze large datasets to identify trends and potential threats.
• Provide actionable insights and recommendations for fraud prevention.
• Collaborate with backend engineering teams and reduce their investigative workload.
• Document findings and communicate investigation results.

Requirements

• 5+ years of experience in Analytics Engineering, Data Analytics, or Fraud Analytics.
• Strong hands-on experience in fraud analysis and forensic investigations.
• Proven ability to identify suspicious activities and attack patterns.
• Strong analytical and problem-solving skills.
• Ability to work independently and take immediate ownership of investigations.

Benefits

• Diverse and technically challenging projects.
• Flexible working hours and a hybrid or remote workplace model.
• Flexible schedule and an Agile/SCRUM environment.
• Technical equipment that you can choose.