Market research is the original data driven business. Incubated and spun-off from a university, we have earned the trust of the world´s biggest companies and leading brands - for more than 80 years. Today, everything at GfK starts and ends with Data and Science
We are proud of our heritage – and our future: Currently we’re on a transformational journey from a traditional market research company to a trusted provider of prescriptive data analytics powered by cutting edge technology. In our Technology & Data organization, we are responsible for the entire lifecycle of our data-driven products.
You still think Market Research is about questionnaires aggregated with Excel?
Wrong! We collect, pipeline, mine and aggregate data at petabyte-scale in our own big data environments and make it available to our Data Scientists with high performance computing solutions. With that the Machine Learning Engineering team owns the responsibility to productize and automate Data Science intelligence.
This is only possible with extraordinary people.
And that’s why we are looking for YOU! A passionate Machine Learning Engineer (m/f/d).
In our Technology & Data business unit, we are responsible for the entire lifecycle of our data-driven products and the division Global Data Science is an essential part of it.
As Machine Learning Engineers, we are part of the Global Data Science division and focus on developing scalable and re-usable machine learning components and solutions at enterprise scale.
Now we are looking for you - a passionate hands-on engineer who is greedy for coding in high-end data science ecosystems!
In that position, you’ll be looked after by Markus, who is a passionate techie with statistical background and a good track record in building actionable data-driven solutions and enterprise scale big data platforms.
Your specific tasks will include:
- Design, develop and implement data science and machine learning models in proof-of-concepts and prototypes
- Develop, optimize, standardize and implement data science and machine learning solutions at scale in data pipelines and distributed systems (e.g. Hadoop/Spark/Kubernetes ecosystem)
- Engineer at scale using service-oriented architecture, containerized applications and functions as a service, especially in cloud service environments (i.e. IaaS, PaaS, SaaS, FaaS)
- Optimize data science and machine learning models using high performance computing (e.g. GPGPU) and real-time techniques (e.g. messaging/streaming services, reactive programming)
- Represent GfK’s machine learning and data science expertise at workshops and conferences
We look for a profile with complementary skills, such as:
- Expert skills with regard to code performance optimization and scalability (e.g., parallelization, sharding, scattering, gathering etc.)
- Solid understanding of service-oriented architectures (e.g. microservices) & distributed systems (e.g. Hadoop, Kubernetes)
- Solid knowledge of cloud computing environments and tooling (AWS, Azure)
- Hands-on experience with scalable machine learning frameworks and general data science tooling required
- Hands-on experience with continuous integration and big data environments required
- Hands-on experience with Docker & Kubernetes required
- Background in a statistical or mathematical field, ideally with a computational element, such as Physics, Data Science, Computer Science is a must
- Experience in development of custom machine learning models from prototyping to scalable implementations would be a strong plus
On top, your English communication skills are great, you are a team-player and tech-obsessed, always on the hunt for the latest and hottest shots!
- OS: Linux (Ubuntu, Debian, CoreOS)
- Programming languages: Java, Scala, C#, C++
- Analytical languages: Python, Spark (Java, Scala, Pyspark, SparkR), R
- ML-Frameworks: H2O, TF, Spark MLlib, Theano, Torch, Caffe, MXNet, Seldon.io
- HPC: CUDA, Numba, C/C++
- Presentation: Jupyter, Dash, Shiny, Vaadin
- Backend: Flask, Dash, Eve, Spring, Spring Boot
- Big Data: Hadoop, Hive, Spark, Accumulo, Nifi
- Messaging/Streaming: Kafka, Flink
- DevOps: Docker, Kubernetes, Bitbucket, Bamboo, Nexus, ELK, Prometheus, Ansible, Terraform
Why else GfK?:
- Any advantages of a Global Player combined with an agile start-up atmosphere
- Annual budget to attend development programs and conferences
- Free language classes
- 30 days holiday per year (plus 24.12 / 31.12.)
- Flexible working hours and the possibility to work from home
- Occupational pensions
- Group Accident insurance also for private life
- Sports and health Management
- Childcare during the summer Holidays
- 5 days paid leave for each child sickness
- Subsidized Canteen / Meals and free coffee/water all the time
- Visa Sponsorship and Relocation service to help anyone moving from abroad
Our doors in our newly built open-concept office space are open for everyone and we are free of stereotyped thinking. The power of our team grows with the variety of individual perspectives and that’s why we need YOU!
Let’s design and shape our exciting future together. Right here. Right now. Together!
Just send an email to MaximilianLink: http://www.gfk.com/careers/jobs-at-gfk/