Leitung Interne IT
2022-10-28 - at Wikimedia Deutschland e.V. in Berlin, Germany Full-time
This job ad has been posted over 40 days ago! (*)
We are looking for an experienced Data Analyst (m/f/d) to join our Software & Development Department. The position is based in Berlin and we offer hybrid workplace options. You will be our first data analyst in the new Wikidata team. In this generalist role, you will be responsible for tracking our product metrics and supporting our product and strategy work with hands-on data science.
As Data Analyst Wikidata, you will be part of an interdisciplinary team and work closely with our Analytics Product Manager Wikidata, and mostly support the Wikidata team. You will work with our product managers, designers, and engineers who build features, products, and services used by hundreds of millions of people around the world. As an experienced and hands-on data analyst, you enable us and our communities to achieve our vision: a world in which every single human being can freely share in the sum of all knowledge.
For background information, take a look at the strategic direction developed for Wikidata and our vision of a Linked Open Data Web.
- You are responsible for tracking our product metrics (in close collaboration with our Wikidata Product Managers and Engineers).
- Support the team to define actionable product metrics
- Implement dashboards to track and visualize product metrics (collaborating with Engineers when needed) and ensure their maintenance
- Ensure continuous monitoring and reporting, and support team sensemaking
- You are responsible for conducting planned and ad-hoc analyses of Wikidata’s users, usage, and content to support our product and strategy work (under the guidance of and in close collaboration with our Analytics Product Manager)
- Support the team to find a fitting approach
- Design experiments/analyses, pull, clean, and analyze data, and collaborate with other researchers
- Create visualizations and reports to document results, communicate with diverse audiences, and support team sensemaking
- You will be our first data analyst in the new Wikidata team and so you will have the opportunity to build up new data processes and batch automation from scratch.
- You will support internal and external research projects, design experiments, and sensemaking sessions with the data perspective (in close collaboration with our Product Managers, Researchers, and Designers).
- You will coordinate contractors and partners supporting our analytics work (in close collaboration with our Analytics Product Manager).
What we offer:
- You will be part of a cohesive and engaged team that fosters unity and supports each other
- Flexible working hours adjusted to the team and people needs
- Work in cross-functional teams towards a common goal
- A working culture that supports releasing a quality product over releasing in order to meet a deadline
- We dedicate one day per quarter in the department to work on self-chosen, non-work-related projects
- Opportunity for personal and professional development
- The possibility of working from home when needed as well as a modern and centrally located office space
- A contract that is not term limited, with the hope and expectation of permanent longevity.
- And a lot more: 30 days of holidays, public transport allowance, access to complementary pension benefits, continued salary in the event of ill children, free-of-cost external life coaching
Learn more about our team by visiting our Wikimedia Tech News Blog.
- You have an academic degree or equivalent experience in data science, applied statistics, quantitative social research, computer science, or related fields
- You have experience with extracting and surfacing value from quantitative data
- You have strong hands-on statistics and data analytics skills (SQL and Python analytics stacks, ideally also some a good knowledge of R) and you are interested in methods suitable for the semantic web
- You have experience with building up new data processes and batch automation
- You are comfortable with self-organizing and working on projects independently
- You have a friendly and helpful nature and can work in a highly collaborative, international, and consensus-oriented environment.
- You are determined to get to the bottom of things and don’t shy away from complex topics.
- You have proficient written and verbal communication skills in English that allow you to communicate complex issues to both experts and lay audiences
- You are comfortable with working in the open: We want our processes to be visible to our community, and all of our work (from code to results) is public and published under a free and open license.
Then apply now! Send us your detailed application documents (Resume & Motivational Letter (yes, we read them) via our job portal. We kindly ask you to refrain from application photos and information on date of birth, marital status and parents. The deadline for the submission of applications is 07.11.2022.
Our HR team will be happy to answer your questions. Please contact us via email@example.com
Wikimedia Germany is committed to equal opportunities and does not discriminate on the basis of, for example, ethnic origin, citizenship, religion or belief, political or other convictions, gender, age, disability or sexual identity or orientation.
About Wikimedia Deutschland:
At Wikimedia Deutschland e.V. we aim to establish and advocate for the creation, collection, and distribution of free knowledge.
In 2004, volunteer Wikipedia activists founded the non-profit association Wikimedia Deutschland in Berlin, which now consists of over 100,000 members and 160 full-time staff.
Free knowledge leads to a fairer world. Wikipedia is the most important online knowledge collection of our time. The German Wikipedia alone records almost 1 billion page views per month for a total of 2.6 million articles. We - Wikimedia Deutschland e. V. - support the volunteers of Wikipedia and its sister projects, develop free software, such as Wikidata, and advocate for free access to knowledge, the opening of education and research, and more common good orientation in data policy.