Freelance SENIOR DATA SCIENTIST
BI Data Science is looking for talented freelance data scientists to collaborate with global data science team and deliver high impact projects.
The freelancer will be working on high impact business cases in close collaboration with a top notch team of data scientists in a very agile environment with focus on scientific problem solving. Currently, multiple projects are available and will start early 2017.
BI Data Science is looking for strong talent with excellent technical skills, analytical skills and business skills. The freelancer will be exposed to high impact projects rendering significant responsibility but will also be supported and enabled by the internal data science team.
Technical skills include experience in unix environments, R, Python and handling data bases. Analytical skills require quantitative experience in scientific research and scientific problem solving as well as advanced statistics, causal inference, probability theory, machine learning and computer science. Business skills include good communication skills and an understanding of business cases as well as a developed sensitivity for change management.
Collaboration and Role. Most of the work will be carried out remotely. However, some visits to Ingelheim, Germany will be required to engage with business teams depending on project demand.
It is anticipated for the collaboration to start in early 2017. Project time frames are typically set to 2-4 months. Multiple projects will be available throughout 2017 and follow-up engagements are possible. Very successful collaborations may lead to long-term or permanent work relationships.
The freelancer will be provided with a BI laptop and will get access to high performance and parallel computing environments depending on project requirements.
Compensation. Compensation will depend on individual project budget and experience, but can be expected to range between 650 – 950 EUR per day.
Further Skill Requirements
- 5+ years experience in at least two relevant computing languages such as R, Python and C++
- Experienced in handling unix environments
- Basic understanding of parallel computing
- Basic understanding of handling unusual data sets such as unstructured data or big data
- Understanding of ETL processes and experience with various data formats
- Experienced in handling various types of data bases including data base operations and understanding of data base concepts and architectures
- Basic understanding of platform and infrastructure architectures and most common interface types
- Well-developed understanding of data hygiene as well as data enrichment
- Basic understanding of web scraping and text processing
- Basic understanding of handling data bases including ability to run queries
- Strong intrinsic appetite to develop technical skills
- Self-driven oversight of relevant analytical fields and analytical as well as technological developments
- Ability to rapidly develop scientific-problem solving approaches to challenging analytical problems including external constraints such as resource limitations, feasibility topics, consumption by business, change management aspects, etc.
- 2+ years of deep analytical problem solving in business environments
- High level of expertise to design, set up and execute validation and experimentation of data science outcomes in business and market environments
- High level of expertise to extract and develop deep analytical insights from complex data sets including identification of patterns.
- Excellent PhD in highly quantitative discipline such as theoretical physics, math, computer science, etc.
- 4+ years of quantitative analytical research
- Demonstrated ability to solve challenging and prior un-solved research questions
- Demonstrated ability to contribute to and develop analytical methods further
- Demonstrated academic excellence
- 3+ peer-reviewed publications
- High level of expertise in relevant methods and skills such as machine learning, advanced statistics, algebra, data visualizaion, artificial intelligence, natural language processing, classification methods, feature extraction, dimensionality reduction, data handling algorithms, regression methods, time-series analysis, predictive modelling, causal inference methods, Bayesian networks, Markov random fields, text analysis, etc.
- Ability to develop, evaluate and apply scientific problem-solving approaches to challenging analytical problems.
- Demonstrated academic excellence
- Strong intrinsic intellectual curiosity and well-established mindset for ongoing development of analytical skills
- Firm expertise and established experience in project management
- Well-developed ability to engage with business users in business lingua and to communicate effectively with different project stakeholders
- Demonstrated ability to quickly understand and adapt to new challenging business questions
- Well-established ability to communicate effectively with various business stakeholders including senior management levels
- Firm ability to quickly evaluate business cases (e.g. back-of-envelope calculus)
- Firm ability to solve business cases with quantitative data-driven analytical approaches
- Ability for out-of-the box thinking and innovative problem solving in business contexts including an entrepreneural mind set
- Strong written and verbal communication skills
- Fundamental understanding of change management principles