We are looking for candidates with an excellent research and publication record and with educational competence within the fields of advanced data science and large databases.
The job will require the consideration of a broad range of technical skills for example:
• Relational and non-relational DB(Database) (incl. graph and no SQL, neo4j, hybrid systems)
• Programming and scripting (Java, .NET, Python, R), statistics (JMP or other SW)
• Visualization and dash boarding (Tableau, PowerBI…)
• Graph theory, Ontology and semantics
• Large DBs (Database), enterprise platforms for big data, Data Warehouses (snowflakes), distributed systems (Hadoop)
• Data pipelining (Pipeline Pilot, Dataiku, or others)
• Data driven modeling (experience with new technology as well as traditional ones)
• Systems integration, API(Application Programming Interface), Dev ops
• The candidate should have some real project experience in Architect, Project lead or implementation lead in past positions
• The job will be focused on developing or setting up new systems at the enterprise level, optimizing those systems, and provide deliverables for selected applications to the
business in order to evaluate alignment and further applicability to other domains.
Job Skills Requirement
• PhD in computer science, data science, applied mathematics, mathematical engineering, physics, geology or a related degree. Experience with Research.
• Experience with materials development from small to relatively large scale. Post-doc and experience in industry is a plus.
• Build relationships with the business in order to understand business objectives and requirements, and translate business needs.
• Strong ability to develop partnerships and relationships across functional areas.
• Good verbal communication skills.
• Team player.
• Ability to propose, implement, lead new approaches and grow new digital capabilities to accelerate materials discovery and development at the interface of discovery
research and material development.
• Ability to convince users to utilize new tools and facilitate their implementation.
• Collaborate with experimentalists and design tools to broadly support and analyze experimental data, as well as to incorporate models from our modeling colleagues.
Apply for the Job