Senior Associate Scientist Statistics and Data Analytics Biotechnology

Job title – Senior Associate Scientist Statistics and Data Analytics Biotechnology (66114)
Location – Delft, the Netherlands  
Job model – Hybrid

Within the Data Automation & Analytics team, as part of dsm-firmenich’s global Science and Research organization, we are looking for an:

 

Senior Associate Scientist Statistics and Data Analytics Biotechnology

 

As Senior Associate Scientist Statistics and Data Analytics Biotechnology you are responsible for the design of experiments, analysis and interpretation of biological datasets to support and accelerate our innovation programs. To achieve this, you will work closely together with our lab automation, strain development and bioprocess experts as well as our analytical colleagues across the globe. You will be part of an entrepreneurial team, playing a vital role in establishing statistical and data analytics approaches aimed at accelerating insight generation and inform decision-making in food and biotech R&D projects. Our activities range from high-throughput screening programs to the development and execution of innovative analytical chemistry approaches, ultimately contributing to nutritional ingredients and solutions enhancing the well-being of people and the planet. This position will report to the R&D manager of the data automation & analytics team.

 

At dsm-firmenich people are at the heart of the company. We are committed to equal employment opportunities and value diversity in the workplace. 

 

Your mission

• Lead and collaborate within and across international project teams, acting as the (bio)statistics expert, to identify key needs and questions that can be addressed using statistics, advanced data analytics and data visualization. 
• Design, plan and execute the analysis of design of experiments, response surface models, control charts, regression models, survival models, time series and related statistical models. 
• Build exploratory and predictive models using multivariate statistics/machine learning/AI methods from, for example, high-dimensional biological and bioprocess data. 
• Visualize, summarize, and communicate findings to project teams and other key stakeholders including but not limited to presentations, reports, publications, and patents. 
• Coordinate data management for projects and collaborate with multidisciplinary team members and external parties in the creation of databases and their connections with data analysis software/webapps. 
• Translate data analytics needs of biotechnology R&D projects into technical requirements for the development of self-service software/webapps for data workflows, analysis, and visualization in collaboration with data and software engineers.

 

We bring

• A rich history and a promising future of bold scientific innovation and passionate creation with our customers. 
• A space to grow by encouraging and supporting curiosity and an open mindset. 
• A culture that prioritizes safety and well-being, both physically and mentally. 
• The opportunity to work for a company where sustainability is much more than a claim and is core to our strategy and purpose. 
• A flexible work environment that empowers people to take accountability for their work and own the outcome. 
• Barrier-free communities within our organization where every employee is equally valued and respected – regardless of their background, beliefs, or identity. 
• Based on your experience we will offer you a base salary of € 62,000 to € 88,000 per year (including holiday allowance and 13th month) and extra benefits, such as 25 holiday days, a bonus, the option to buy more holiday days with a 6% my choice budget and much more. Please be aware that the salary may vary based on your experience.  

 

You bring

• Ph.D. in (Bio)Statistics, Data Science, Computer Science, Physics, Biotechnology or a related quantitative discipline field with 3 years additional work experience or a master’s degree in Statistics, Data Science, or related quantitative discipline with 5 years’ additional work experience. 
• Experience in applied statistics, data management, data reporting and visualization and experience with machine learning/AI algorithms to R&D data. 
• Experience with statistical software packages and modern data visualization tools.  
• Experience in Python and/or R programming.  
• Knowledge on setting up data models and databases (SQL, NoSQL) and accessing them using queries. 
• Expertise in building and running data processing workflows and webapp creation tools and libraries is a plus. 
• Experience in FAIR data management, advanced data processing pipelines, data integration and visualization using cloud-based platforms (e.g., AWS, Azure) is consider