Data Scientist (VIN Pattern Engineer)
Softeta is seeking a data scientist to analyze vehicle identification numbers and develop reliable decoding rules, working with large datasets and combining analytical thinking with python, sql, and ai-assisted tools, to identify recurring patterns and deliver custom software solutions.
Skills required
About this role
Softeta is a software engineering partner for finance, energy, industrial, and other high-stakes sectors. We specialise in building and modernising 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 are looking for a highly analytical Data Scientist (VIN Pattern Engineer) to analyse Vehicle Identification Numbers (VINs) alongside known vehicle attributes, identify recurring patterns, and develop reliable VIN decoding rules.
In this role, you will work with large and sometimes unstructured datasets, combining analytical thinking with Python, SQL, and AI-assisted tools to improve the accuracy and reliability of VIN decoding.
Key Responsibilities
- Analyse VIN and vehicle attribute data to identify recurring patterns and relationships.
- Maintain existing patterns and investigate decoding errors, inconsistencies, and conflicts.
- Use existing AI agents and develop Python and SQL scripts for data analysis and validation.
- Deploy verified VIN patterns into production and monitor their accuracy.
- Collaborate with another VIN Pattern Engineer and the Data Engineering and Analytics teams.
Requirements
- 4+ years of experience in a similar data-focused role, such as Data Scientist, Data Analyst, Analytics Engineer, or Data Quality Engineer.
- Hands-on experience with Python and SQL.
- Ability to work effectively with large, complex, and sometimes incomplete datasets.
- Attention to detail and a structured approach to data analysis.
- Familiarity with AI agents and AI-assisted data analysis.
- Good communication and teamwork skills.
Benefits
- Diverse and technically challenging projects.
- Training budget for professional and personal growth.
- Flexible working hours.
- Flexible schedule and an Agile/SCRUM environment.
- Technical equipment that you can choose.
- Salary range - 3500 EUR to 5000 EUR monthly (gross).
