As a data scientist, you will:
Design and scope data science projects: Work with business owners to define big picture objectives, key actionable insights needed. Translate requirements into meaningful projects, including business case.
Develop business awareness: Awareness (and outside-in application) of the latest business trends, use cases, modeling capabilities, within the FMCG industry and the FrieslandCampina organization
Analyze data using different methods: Analyze data with different statistical methods, interpret results and provide clear summary conclusions, present data analyses to senior management, preferably in interactive dashboards, with a clear story line.
Assure our data process: Develop a deep understanding of FrieslandCampina databases and transactional systems. Collect, research and analyze data to assure integrity of project data, including data extraction, manipulation, processing, storage, archival and data analysis for appropriate usage in databases.
Develop, manage and maintain our digital assets: Work towards a production-ready version of machine learning models (or traditional ones). Testing, scaling, refactoring and security is your responsibility as well. As such, you have a good understanding of software engineering.
Share knowledge and training: Share knowledge and information of analysis techniques and data coding with other staff and train, if needed. Develop our internal community of business analysts.
Share principles and qualities: Value operating in a collaborative and cooperative environment, adhere to all principles of confidentiality, show initiative, solid judgment and resourcefulness.
For thousands of people every day, we are more than just a dairy company. To our farmers, our employees, the communities we serve, the businesses we work with and the people to whom we bring happiness, FrieslandCampina means something more. For them it’s not just about what we do, but who we are.
We value talented people from any background who want to contribute to something bigger than themselves. We encourage all of our 22,000 employees to make decisions that benefit our entire company. At FrieslandCampina we own our own career and act accordingly. We trust you to make a difference in your job and influence the bigger picture. Working at FrieslandCampina means you are contributing to a better world.
To be a successful in this position, you are/have:
Bachelor’s degree in a Quantitative Field (Computer Science, Mathematics, Engineering, Economics, Business, Finance, etc.) Master’s degree is preferred.
- 5+ years of relevant work experience, including:
- Relevant experience with fundamental statistical analysis tools and techniques; including statistical languages (like R or Python + Pandas).
- Relevant experience with time series forecasting, optimization methods, business analytics and data mining.
- Relevant experience creating and maintaining production-ready software, starting from scratch or based on a prototype.
- Working knowledge of scripting, ETL design and SQL. Familiarity with database modeling and data warehousing principles.
- Experience with Big Data technologies like Hadoop & Spark would be a plus.
- Experience working at Pricing and/or Revenue Management would be a plus.
- Familiarity with agile principles (e.g. Scrum), facilitating workshops and prototyping.
- Excellent communication skills (verbal and written) to communicate with clients and team, prepare + deliver effective presentations
- High level of professionalism, energy and sense of urgency to “make things happen.”
- Ability to manage multiple tasks and work towards long-term goals.
- Strong analytical and problem solving skills
- Self-motivated and highly ambitious
Your salary is based on the weighting of your job, your experience and your training. FrieslandCampina offers not only a competitive salary but also training and education on the job because it’s important for our people to continue to grow. After all, your development is not only good for your career; our products also benefit from it. The mutual exchange of knowledge between colleagues is also evident on the work floor. It is, after all, the most effective way to learn.
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