À propos de ce poste Data Scientist chez PwC
Job Description & Summary
About the team
We help our clients detect financial crime by assessing, optimising and implementing their monitoring systems. Our team serves as a regional centre of excellence that provides technical advisory to clients mainly in Europe but also on other continents. To enable us to deliver results rapidly, we have developed several cloud-based applications that we strive to constantly improve and expand.
Come and join our fast-growing team of Data Analysts/Engineers/Scientists and AML Compliance Experts and help us combat money laundering and other types of financial fraud.
About your manager
Liviu Chirita is Partner responsible for PwC CEE Financial Crime Advisory. Originally with a background in financial services risk management, he has led an expansion of the current team into wider Risk & Regulatory topics including digital and technology related support to PwC clients. The existing multi-national team is predominantly Prague based.
Job description & summary
80% Work on client engagements
Analysing data mainly about customers and their transactions
Providing methodical guidance to clients
Transforming data and understanding its business meaning
10% Development our digital assets
Creating machine learning pipelines
Developing new forms of visualisations
Programming in Python including writing tests
5% Preparing new engagement proposals
5% Staying up-to-date with developments in the field of machine learning
What matters to us
At least bachelor degree in Data Science or a similar field
Understanding of machine learning algorithms for classification and clustering and various mathematical optimisation methods like differential evolution
Knowledge of Python, Git and SQL
Outstanding English both verbal and written
Willingness to learn, take initiative and be challenged, confident communicator and a strong team member, with willingness to travel if needed
What will help you stand out
Experience with tools for distributed processing is a plus - Dask, Spark
Experience in the field of Anti-Financial Crime or Banking is a plus
Understanding of neural networks and graph algorithms is a plus
Knowledge of natural language processing might be beneficial
Why you’ll enjoy working here
Professional growth that matches your ambitions and pace. Gain in months the kind of experience that can take years to build elsewhere.
Fair pay with no gaps. We are among the few companies in the Czech Republic certified for Equal Pay.
A flexible benefits programme with 30,000 points (for senior 45,000 p.) to spend on what matters most to you.
30 days of paid time off, including three well-being days and two additional days off at the end of the year.
An opportunity to give back to the community with one paid volunteering day every year.
The chance to work from one of PwC’s international offices (available from the Senior Associate level).
We support your learning and development journey: We offer training in business skills (such as presentation and communication skills, assertiveness, and giving feedback) as well as digital skills (including Alteryx, Power BI, and AI). We also cover the cost of professional certifications, such as CFA.
A buddy programme, regular feedback, and access to a coach who can support your professional development and career path.
Extensive well-being support and initiatives promoting a healthy lifestyle, from Dr. Digital and Human Dynamic programmes to workplace yoga and running events.
An ultrabook and an iPhone with unlimited data.
At PwC, we help clients solve today’s and tomorrow’s challenges across audit, consulting, tax, legal, technology, and data. We create an environment where people can learn, grow, and build a career in their own way. We believe the best results come from diverse experiences and perspectives. That’s why we foster an inclusive culture where everyone can be themselves, build on their strengths, and contribute to work that makes a real impact.
Interested in joining us? We’d love to hear from you and tell you more about this opportunity.
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