At a Glance
- Tasks: Design and build data pipelines, write Python scripts, and collaborate with customers on technical solutions.
- Company: Rapidly growing Scientific SaaS company revolutionising R&D in science-driven industries.
- Benefits: Competitive salary, hybrid work model, and opportunities for professional growth.
- Other info: Join a dynamic team at the intersection of science, data, and software.
- Why this job: Make a real impact in the scientific community while working with cutting-edge technology.
- Qualifications: Experience in Python, SQL, and handling large datasets; degree in Computer Science preferred.
The predicted salary is between 60000 - 100000 £ per year.
Salary: £60,000 - 100,000 per year
Requirements
- Experience using Python in a professional environment, including framework experience
- Working knowledge of SQL and relational databases
- Experience handling and manipulating large datasets, ideally scientific or experimental data
- Interest in working in a customer-facing, implementation-focused engineering role
- Degree in Computer Science or a related field
- Experience integrating data from lab equipment or scientific instruments is a plus
- Familiarity with Excel or other analytical tools is a plus
- Exposure to SaaS, data platforms, or startup environments is a plus
Responsibilities
- Design and build custom data ingestion pipelines between customer systems and our platform
- Write Python-based integration scripts using modern Python frameworks
- Work with large scientific datasets, including structured and semi-structured lab data
- Perform data transformation, validation, and manipulation to support downstream analysis
- Collaborate with implementation, customer success, and scientific stakeholders to understand customer workflows
- Support complex customer onboarding and expansion projects through tailored technical solutions
- Develop data integrations for customers, such as ingesting data from lab equipment and setting up automated data transfer routines
We are a rapidly growing Scientific SaaS company that has developed a unified LIMS platform for enterprise R&D teams in chemicals, materials science, pharmaceuticals, and other science-driven industries. Our platform helps teams manage experimental data, connect lab systems, and apply advanced analytics and AI to accelerate innovation. This is a hybrid role based in London, and you will join our Customer Implementation team working at the intersection of science, data, and software, where your work will have a direct and visible impact on how real-world R&D is done.
Software Engineer Chemistry & Data Integration employer: Sivara GmbH
As a rapidly growing Scientific SaaS company based in London, we offer an exciting opportunity for Software Engineers to work at the forefront of innovation in the R&D sector. Our collaborative work culture fosters creativity and growth, providing employees with tailored development opportunities and the chance to make a tangible impact on scientific advancements. With competitive salaries and a focus on customer success, we are committed to supporting our team members in their professional journeys while enjoying the vibrant atmosphere of one of the world's leading cities.
StudySmarter Expert Advice🤫
We think this is how you could land Software Engineer Chemistry & Data Integration
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We think you need these skills to ace Software Engineer Chemistry & Data Integration
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Sivara GmbH, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Sivara GmbH. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Sivara GmbH
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Sivara GmbH!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
