Data Scientist Remote
Job description
Vertex Solutions has been providing excellent services to our clients in Enterprise Software, FinTech, Insurance, Mobile, R&D, Finance, and IT since 1997. We work for some of the most innovative names in their respective markets.
We operate as partners from a position of trust, developed through our delivery of essential talent time and time again. We have helped to build talented teams of scientific staff and engineers (in Software, Hardware, IT, and Network Support disciplines) from graduate through to board level, allowing our clients to create value and develop their brands.
We provide some of the best technology talents in Europe to a mix of global brand names and cool technology start-ups.
Are you looking for a new challenge as a Data Scientist?
Our client is one of the largest Financial Institutions and Financial Services organizations in the world, with operations in 64 countries and territories.
Using technology to transform the world’s leading financial institution, this is a job for the boldest problem solvers in the tech industry.
Responsibilities:
- Development of probabilistic models to quantitively measure the performance of the individual cybersecurity controls, identification of failure modes for cybersecurity controls and selection of proper distributions to characterize these failure modes.
- Analysis of multiple internal data sources primarily with Spark on Data bricks platform to support modelling process.
- Together with cybersecurity experts development of threat models (kill-chains) and coding them as stochastic simulations.
- Development and maintenance of data pipelines that feeds data into the threat models.
- Development of methods for calibration of expert opinions to properly estimate the model parameters.
- Development of numerical libraries used to build threat models (Python, Pytorch, Pyro, Numpy).
Skills Required:
- Must have: degree (MSc, PhD) in Statistics, Applied Mathematics, Physics or related quantitative discipline.
- Must have: proven experience with one or more of the following: operational risk modelling/economic capital modelling, probabilistic risk assessment, reliability engineering, decision research, experience in using Bayesian Networks/Influence Diagrams/Markov Decision Processes, Bayesian inference methods, uncertainty quantification.
- Strong programming skills in Python.
- Nice to have: hands-on knowledge of one of the following libraries: pyro, pymc3, Stan, Win BUGS, Tensor Flow Probability, PyAgrum or any other Probabilistic Programming Language.
- Good understanding of probability theory, random variables and their distributions, monte-carlo simulations and inference algorithms.
- Experience in analyzing big volumes of data, preferably with Spark. At least basic knowledge of SQL.
- Interest in MLOps and Model Risk Management practices.
- Motivation to develop in the emerging field of cybersecurity risk modelling.
- Strong intellectual/analytical potential and willingness to the goal of extending the existing risk models and to perform original applied research in the field.
- Knowledge of Git, Confluence, JIRA, understanding of agile methodologies.
- Ability to clearly articulate technical topics in English, both written and spoken.
Employment type: B2B
Benefits:
- Private medical care and life insurance
Other benefits:
- Highly skilled tech team who is always ready to help, collaborate and share knowledge
- Clear career engineering path and the possibility to rotate between projects and teams (for longer term)
- Occasionally Hybrid working model after the Pandemic (we miss each other a lot!)
Have we sparked your interest?
Get in touch! We are looking forward to speaking to you.
Reach out to me at [email protected] or apply for this job to know more!
