Big Data Scientist
- As a data scientist you build models that transform the way companies make business decisions. You let the data and statistics dictate the decision instead of gut feeling and seniority.
- The mission of a data scientist is to build intelligent scalable algorithms that help companies to generate new insights and increase business value.
- A data scientist must be able to answer complex statistical questions and be able to process large amount of data to obtain those answers.
- A data scientist effectively communicates his results. This includes visualizing data or results in a dashboard. That is why a data scientist should be well-versed in creating charts and graphs. Next to visualization, a data scientist should also be able to adequately report his results and insights verbally and in writing.
- As a data scientist you love to discover interesting data patterns using techniques like text mining and classification. You also love to optimize logistic processes and to build models that predict future values based on historic (real-time) data.
- Rather than developing a model or algorithm in isolation, our data scientists like to embed their models in the existing systems and infrastructure of our clients.
- A data scientist works with Big Data Engineers and Big Data Infra Specialists to deliver full stack big data solutions.
- BA/BS/MS/or PhD, with strong academic record, ideally in Artificial intelligence, Economics, Mathematics, Computer Science, Physics, Operations Research, Statistics or other quantitative field.
- Good understanding of Mathematics, Statistics, Algorithms, Data structures, Data
Visualization, Machine Learning and modeling.
- You don’t blindly follow assumptions but you understand the strengths and weaknesses of different models and can effectively reason about when to apply various combinations.
- You’re not a one trick pony, which means you are able to flexibly adapt your models and where you implement them as situations change.
- Experience with Python, SQL, etc.
- Affinity with data analysis software such as: R, SAS, STATA, Julia, Mathlab.
- The ability to provide analytical, creative, and innovative solutions to complex problems.
- Experience with big data platforms: NoSQL databases, MapReduce techniques, Kafka, Storm, Hadoop / Hive / Pig.
- Experience with natural language processing like: Sentiment analysis, TF/IDF.
- Experience with visualizing models and its findings such as: D3JS, AngularJS, HTML, CSS, Tableau.
Our client has a consultancy company in the area of big data engineering, data science and data architectures. In all these segments of big data, they provide consultancy, training & support. They help customers in their transition from previous generation information architectures to the new generation of big data technologies and analytics.
Our client distinguish ourselves by providing their customers with future proof, sustainable solutions that are able to grow and adapt as their company does. Our client consultants have the scientific background but are pragmatic in the execution and understand it all comes down to business value. Our consultants are industry experts and thought-leaders who have worked extensively with big data technology.