Do you want to be a key player in taking Vattenfall forward in the emerging energy landscape?
The energy sector is undergoing revolutionary change. Digitalization and the Internet of Things opens up new opportunities such as remote monitoring of distribution networks, increased efficiency and flexibility of production plant through automation and increased transparency and control for end users. Rapid increase of bandwidth, processing power and data storage capacity creates possibilities and demand for new methods to extract and analyze information.
Vattenfall R&D has group-wide responsibility for conducting business driven technical development that supports the company’s strategic focus areas. We are now looking to grow our in-house data analytics capabilities with another Data Scientist.
We offer you a flexible work environment and the opportunity to work and develop in an exciting and rapidly changing technical field of strategic importance to the company.
Participate in pre-studies and proof of concepts for development of new business opportunities based on internal and external data.
Solve client analytics problems and communicate results and methodologies.
Collaborate with business domain experts to identify data sources and collection processes. Work with IT teams for data collection, integration and retention. Design and develop infrastructure, logic, intelligence, user interface and automation needed to transform data and distribute it to users.
You hold a Master of Science degree (or higher) in Computer Science / Engineering / Quantitative modelling and analysis (e.g. statistics, econometrics) and/or possess corresponding work experience.
The data analytics team that at present consists of 5 individuals need to deal with a wide variety of analytical problems. Hence, the ideal candidate has both some width and some depth to his or her data science tool box. Furthermore, as we do a lot of exploratory analysis and prototyping, candidates need to be comfortable building algorithms and models from scratch.
Candidates should be proficient in at least three of the following areas:
Feature engineering/Data mining
Time series analysis
Predictive modelling/Machine learning
Deep learning/Artificial Intelligence
Sensitivity analysis/Model validation
The following competences are not obligatory, but are still valuable within the team:
Data engineering/Data stewardship
Big data platforms/Cloud computing
Data-driven product development
You are analytical, inquisitive, committed and self-driven with good communication and interpersonal skills. Fluency in English is a prerequisite, a good command of Swedish is desirable.
LANGUAGES & PLATFORMS
Vattenfall uses Microsoft Azure as its platform of choice. Data will be stored and managed in Azure. The computations, analyses, and number crunching we do can use other platforms or services if need be, but results need to be piped back to Azure.
The data science team mostly do models in R, but proficiency in other languages is acceptable. We will (hopefully) move to Julia in the near future for everything computationally intensive; experience with Julia is a bonus for any candidate.
We are convinced that diversity contributes to building a more profitable and attractive company and we strive to be good role model regarding diversity. Vattenfall works actively for all employees to have the same opportunities and rights regardless of gender, ethnicity, age, transgender identity or expression, religion or other belief, disability or sexual orientation.
Location Älvkarleby or Stockholm (Solna)
For information about the position please contact Jonas Alin, Section Manager, Data Analytics & ICT Solutions +46 702 11 79 53. For information about the recruitment process you are welcome to contact recruiter Caroline Grammenos, +46 722 24 97 01.
Union representatives in Sweden
Pernilla Owe (Akademikerna), Anders Bohlin (Unionen), Christer Gustafsson (Ledarna) and Ronny Ekwall (SEKO). You can contact them via the main switchboard +46-8-739 50 00.
We look forward to receiving your application with CV and cover letter via this page, no later than 24 November 2017.