- Job Title: Quantitative Developer
- Salary: Not Disclosed
- Location: 5900 Hurontario St, Mississauga, ON L5R 0B8
- Company: Citi
- Qualification: Graduate
- Experience: 2-4 years
- Job Type: Full-time
ABOUT CITI
Citi, or Citigroup Inc., is a global economic services organization presenting a huge range of banking services and products. Headquartered in New York, Citi operates in more than one hundred international places, imparting retail banking, investment banking, wealth management, treasury and trade solutions, and organization services. The enterprise serves loads of lots of customers through its patron banking divisions, and its institutional clients encompass multinational corporations, governments, and economic establishments.
Citi is thought for its progressive virtual banking answers and global reach, making it considered one of the largest and most diverse economic establishments globally. With a robust dedication to sustainability and social obligation, Citi focuses on using monetary inclusion, lowering its environmental impact, and fostering community improvement. Citi’s lengthy data, dating back to 1812, displays its non-stop evolution and management inside the financial services enterprise.
Job Overview:
A Quantitative Developer designs and implements complex mathematical fashions and algorithms to aid buying and promoting strategies, change management, and financial analysis. They art work cautiously with quantitative analysts to translate mathematical theories into inexperienced code, frequently in languages like Python, C++, or Java. Their responsibilities encompass growing pricing models, backtesting techniques, optimizing performance, and integrating systems inner a business enterprise’s infrastructure. Strong skills in arithmetic, data, and programming, on the side of knowledge of economic markets, are vital for achievement in this position. The function regularly requires advanced degrees in quantitative disciplines.
Requirements and Skills for a Quantitative Developer:
- Educational Background
- Advanced Degree: Typically, a Master’s or Ph.D. In a quantitative field together Computer Science, Mathematics, Physics, Engineering, Financial Engineering, or an associated situation is fantastically favored.
- Strong Academic Foundation: A deep expertise in advanced mathematics, opportunity concepts statistics, and numerical techniques is critical.
- Programming Skills
- Proficiency in Programming Languages: Expertise in languages like Python, C++, Java, or MATLAB is important. Python is frequently used for information evaluation and prototyping, at the same time as C++ is favored for high-general performance algorithmic buying and selling structures.
- Software Engineering: Ability to jot down down easy, maintainable, and optimized code. Understanding software layout patterns and debugging techniques is essential.
- Familiarity with Libraries: Experience with libraries like NumPy, Pandas, SciPy, and TensorFlow for Python, or Boost and Eigen for C++ can be fantastically useful.
3. Mathematical and Statistical Expertise
- Quantitative Modeling: Ability to broaden, put into effect, and refine quantitative models used for pricing, management shopping, and promoting techniques.
- Statistical Analysis: Knowledge of statistical strategies, time series evaluation, and econometrics is needed to research large financial datasets and increase predictive models.
- Machine Learning: An information system getting to know techniques together with supervised and unsupervised mastering, reinforcement reading, and neural networks can be a big asset.
4. Knowledge of Financial Markets
- Understanding of Financial Instruments: Familiarity with economic products inclusive of derivatives (options, futures, and so forth.), regular-profits gadgets, and equities is critical.
- Risk Management: Knowledge of marketplace chance, credit score risk, and operational risk, similar to hedging techniques, is essential in growing systems that manipulate those risks correctly.
5. Analytical and Problem-Solving Skills
- Data Analysis: Strong potential to analyze and extract meaningful insights from big, complicated datasets.
- Algorithmic Efficiency: A focus on optimizing algorithms for speed, scalability, and robustness, particularly under real-time or immoderate-frequency buying and selling conditions.
- Communication and Collaboration
- Team Collaboration: Ability to interact efficiently with quantitative analysts, traders, and extraordinary technical professionals to translate business requirements into technical solutions.
- Communication Skills: Clear verbal exchange of complex technical ideas to non-technical stakeholders is crucial.
- Experience and Domain Knowledge
- Prior Experience: Experience walking in economic services, trading organizations, or investment banks is regularly required. Internship or previous employment in a quantitative function is favored.
- Domain-Specific Knowledge: A genuine know-how of marketplace microstructure, monetary rules, and financial standards complements a candidate’s fee.
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