lead a small team responsible for design, build, deploy and supporting SaaS services
empower and help the team in efficient design, development, delivery and production-support
enable learning culture, promote continuous feedback and improvement
insurwave is a client centric, tech focused, disruptive company that provides a digital pathway for commercial lines of insurance. We are passionate about our people and our values of trust, curiosity and quality are embedded in everything we do
deliver high quality solutions using fully automated processes
work with business areas to ensure that built solutions are aligned to requirements, delivered according to plans and developed with expected quality and security standards
work closely with Product Owner to ensure that requirements are well understood by the team and developed solutions are properly demonstrated to the Product Owner before delivery
Salary
salary
Requirements
experience of leading development teams working in agile development model
exceptional communication and leadership skills, demonstrated ability to form effective working teams and maintaining healthy, learning culture within it
experience with CI/CD pipelines, TDD and pipeline automation
very good experience with various testing stages for APIs
in depth understanding of microservice architecture and how to use it to build applications
knowledge of good practices, design patterns and SOLID principles
good understanding of application design and strong problem-solving skills
knowledge of .NET stack - C#, ASP.NET Core Web Apis, LINQ, asynchronous and parallel programming, dotnet tools
process engineer
Working hours
permanent
Responsibility
design, build and maintain automated document extraction solutions
establish framework for systematic QA and monitoring of the automation solution
analyse high volume of documents to understand variability and extract standardisation patterns
maintain and report on statistics of performance, errors, exceptions, failure cases, edge cases etc
constantly curate and build datasets for benchmarking and regression testing
work closely with AI product manager to review performance monitoring report and analyse datasets to inform improvement needs
collaborate with data analysts, data engineers, data scientists and other business areas to ensure that built solutions are aligned to requirements, delivered according to plans and developed with expected quality and security standards
Requirements
experience with process assessment and development of automation solutions with focus on document extraction and standardisation
strong problem solving, design, and analytical skills
strong technical experience in the areas of data standardisation and analysis
exceptional logical thinking and methodical approach to find solutions for complex problems
excellent attention to detail and passionate about quality
strong understanding of regular expressions
familiarity with OCR and document extraction tools
familiarity with APIs integration and operating principle
data scientist
Working hours
permanent
Responsibility
develop and deploy production-ready data science code and models using fully automated processes
build high performing AI/ML models that meet business defined performance metrics
continuously improve the owned services’ performance, security, architecture, and maintainability
provide technical leadership to junior data scientists
ensure the team is working according to defined best practises, standards and processes
enable learning culture, promote continuous feedback and improvement
work closely with AI product manager, platform engineers, ML engineers and software developers to establish ML Operations framework and contribute to overall architecture design
collaborate with data analysts, data engineers, data scientists and other business areas to ensure that built solutions are aligned to requirements, delivered according to plans and developed with expected quality and security standards
Requirements
experience in Data Science / Machine Learning
experience in delivering data science projects to live in an industry production environment
A proven ability to solve complex problems with demonstrable ability to learn new business concepts and domains quickly
experience with leading/supporting ML Operations
in depth understanding of common Machine learning problems as well as good understanding of mathematical foundations of ML algorithms
experience of Deep Learning Architectures and popular deep learning frameworks
expertise using multiple open source machine learning libraries
experience in working with unstructured, semi-structured and structured datasets