Risk Quantitative Analyst/Machine Learning
Voted the Most Desired Employer in Romania, in the Financial Services Industry, three consecutive times, in the Catalyst surveys, Deloitte Romania provides services in audit, tax, legal, consulting, financial advisory, risk advisory, business processes as well as technology services, through 2,000 professionals. The Regional Audit Delivery Center (RADC) provides Audit services to various Country Member Firms from Deloitte Central Europe and to their clients. The Tax & Legal Delivery Center (TLDC) offers services focused on 5 service lines: GES (Global Employer Services), Business Tax, Global Tax Center Europe, Global Trade Advisory (GTA) and Legal Center of Excellence (CoE).
Worldwide, Deloitte serves four out of five Fortune Global 500 companies through a globally connected network of member firms in more than 150 countries and territories, with over 330,000 professionals. The organization is recognized among “World’s Best Workplaces™” by Great Place to Work® and Fortune and among “World’s Most Attractive Employers”, by Universum, according to 2020 surveys.
We believe that innovation comes from contrasting disciplines, backgrounds and cultural perspectives and that the innovative solutions our people deliver have to always make an impact that matters. We celebrate individual strengths and we prioritize our people’s well-being.
You bring the ambition, we’ll provide the opportunities.
• 2-3 years’ relevant experience working in a financial institution or a related field in a relevant risk or quantitative position such as: market risk, financial supervision, credit or financial modelling, or a role in machine learning, data science or econometrics applied to any field;
• Strong academic background: degree in Data Science, Business Analytics, Statistics, Mathematics, Engineering, Computer Science, Econometrics or related field with strong a quantitative focus;
• Master’s degree in a quantitative discipline is preferred but not mandatory;
• Good knowledge of programming, e.g. SAS/R, SQL, VBA and Microsoft Office tools
• Working knowledge of Python and machine learning associated libraries e.g. numpy, pandas, matplotlib, sklearn, keras, pytorch, nltk or alternative libraries (including in R or MatLab).
• Working knowledge of basic supervised Machine Learning models: linear/logistic regression, random forests, boosted trees (xgb), support vector machines, neural networks.
• Familiarity with unsupervised models e.g. clustering, dimensionality reduction or natural language processing is an advantage
• Experience in exploratory data analysis and modelling cross-sectional and time-series data
• Strong multi-tasking and project management skills;
• Excellent English written and oral communication skills;
• Participate in the design, implementation, calibration, and validation of models;
• Document models, methodologies, analyses, and findings;
• Assess the quality of data underlying risk models and model calibration;
• Engage with client representatives to obtain an understanding of risk practices and assess them;
• Provide support to clients in the areas of internal governance, policies and frameworks in place linked to quantitative risk management;
• Interpret new regulatory requirements focusing on those specific to internal models.
The successful candidates will work alongside other subject matter experts in the FSI Risk and regulatory department and will be part of an international team with substantial knowledge of laws and regulations in accounting, risk and advisory as well as best practices in banking supervision.
The role offers the opportunity to build on and continue developing your existing knowledge and skills, and to progress more senior levels as well as contribute directly to the continued growth of the business line.