For us, Scientific Computing is any type of processing which requires advanced algorithms to solve a business problem. A problem might require Optimization, which allows us to maximize the income or minimize the cost for our client, given some boundary conditions. An example could involve using Genetic Algorithms to establish optimal (in terms of cost) logistics for a transport company. Or applying Linear Programming to compute the risk of a loan for a given loan-taker (and suggest ways to minimize the risk).
A dedicated team is allocated to each of the projects we take on. Each team has all it takes to successfully carry out the project, including:
- Software Development expertise in the selected tech stack,
- AI / Machine Learning, Optimization or Scientific Computing expertise in the required domain,
- testing/validation capability,
- high-level technical expertise (Big Data, Architecture, Hosting, Cloud, Performance, Maintenance),
- bandwidth to execute the project in a timely fashion,
- full professional proficiency in English of all team members.
We work with Kanban in an Agile spirit.
We are flexible in terms of the communication style adopted in a project. Both seamless contact and discussing a demo once every two weeks are fine by us. We typically get in touch in order to report our status and to cater for evolving requirements or changes in timelines. We are available via phone, e-mail, Skype, Slack, Zoom, Google Meet, etc.
- First and foremost, good software is built by good professionals. Thus, recruitment to the group is very strict. For example, for a software development position we investigate a candidate's background, technical knowledge, coding style, programming aptitude, code neatness, communication skills and completeness of one's solutions. As a result fewer than 5% of candidates get admitted.
- Second, we peer-review our code and we employ the industry's best practices by using version control, design patterns, DRY, etc.
- Third, our code is always tested and continuously improved.
We are skilled in:
We also use NoSQL and relational databases for persistence. We are happy to take on a project in a technology that's not on this list. We are fast learners.
12 hours or less. Feel free to contact us anytime.