Quantitative Analytics Senior Job Description
Quantitative Analytics Senior Duties & Responsibilities
To write an effective quantitative analytics senior job description, begin by listing detailed duties, responsibilities and expectations. We have included quantitative analytics senior job description templates that you can modify and use.
Sample responsibilities for this position include:
Quantitative Analytics Senior Qualifications
Qualifications for a job description may include education, certification, and experience.
Licensing or Certifications for Quantitative Analytics Senior
List any licenses or certifications required by the position: ACAMS, CIA
Education for Quantitative Analytics Senior
Typically a job would require a certain level of education.
Employers hiring for the quantitative analytics senior job most commonly would prefer for their future employee to have a relevant degree such as Master's and Bachelor's Degree in Statistics, Economics, Mathematics, Finance, Computer Science, Engineering, Sciences, Management, Quantitative Finance, Science
Skills for Quantitative Analytics Senior
Desired skills for quantitative analytics senior include:
Desired experience for quantitative analytics senior includes:
Quantitative Analytics Senior Examples
Quantitative Analytics Senior Job Description
- Providing leadership and guidance to ensure that TFS continues to employ valuation best practices by benchmarking internal derivatives, asset and liability models, methods, inputs and processes against the latest industry standards
- Enhancing the team’s capability to integrate and support the valuation and risk measurement of new, complex funding and hedging products into our core valuation application
- Developing a comprehensive analytics and reporting platform to ensure an in-depth understanding and explanation of all derivative, asset and liability valuation drivers, assumptions and results is obtained, and to explain periodic changes in valuation through the use of a risk-factor sensitivity based framework
- Ensuring that TFS continues to employ a robust Independent Price Verification (IPV) process to manage the validation of all relevant valuations, and that the team has a framework for adequately researching, resolving and documenting any discrepancies
- Assisting in the development of valuation bench-strength and expertise across the spectrum of current and future financial products
- Partnering with our Japanese parent and sister global treasury departments as part of the global “Valuations Center of Excellence” to identify opportunities to improve treasury valuation capabilities or results by leveraging best practices, tools, analytics, procedures and methods
- Analyzing large, complex, disparate data sets to identify actionable insights for senior executives
- Assisting with large-scale data collection efforts through administration of multi-national panel surveys
- Building benchmark and other standardized data reports for members with simple and insightful graphics
- Conducting basic descriptive analysis robust inferential analyses, including correlation, factor analysis, and multiple regression
- Working as a risk professional, preferably in a major financial institution, for a minimum of 6 –years
- Hands-on experience in data mining and developing quantitative PD, LGD, EaD based on logistic regression or other econometric techniques (Value-at-Risk, Stress-testing)
- Hands on experience with Stress Testing model development
- Working knowledge of ICAAP/ORSA
- Analytical/quantitative background
- PhD degree in quantitative field (Finance, Math, Engineering)
Quantitative Analytics Senior Job Description
- Present strategic research and benchmarking analysis findings to clients
- Responsible for data extraction and quantitative analysis on a portfolio and trust level basis
- Drill down into data to find root causes of trends
- Combine appropriate qualitative information as necessary to develop insights and formulate recommendations
- Effectively communicate results of analysis to key business partners to gain support of conclusions
- As necessary, develop and enhance origination and portfolio trend reports to help identify segments that require more in depth analysis
- Write queries, pull data, and assemble reports and presentations
- Perform validation of Fraud and Anti Money Laundering (AML) models in compliance with the Bank's Model Risk Policy
- Develop independent benchmarks using supervised and unsupervised learning algorithms and/or classical statistical approaches
- Prepare detailed technical reports describing the mathematical analytics of the model, validation techniques employed, test results obtained, and any model limitations noted
- Graduated from a reputable higher education institute
- Experience in, and familiarity with, CCAR models (audit, validation, or developing)
- PhD Degree required in Engineering, Mathematics, Applied Computer Science, Applied Management Science or Operations Research plus experience in advanced quantitative analysis and modeling
- More than 2 years of actuarial experience preferred
- Candidate who is pursuing FSA through the Quantitative Finance and Investment (QFI) track is preferred
- Advanced level Excel VBA and SQL Server knowledge is a plus
Quantitative Analytics Senior Job Description
- Ability to explain complex actuarial and financial modeling techniques in a simple and concise way
- Establish and maintain productive working relations with internal stakeholders and vendors
- Play a key role in ensuring the appropriate use of risk models
- Research best practices and stay current in knowledge of Fraud and AML risk management methodologies and development in the field of quantitative analysis, and share knowledge with business partners and senior management
- Ensure the appropriateness of the models for their specific use, reasonableness of the model assumptions and the accuracy of the model implementation
- Prepare detailed technical reports describing the modeling approach are conceptually sound, validation techniques employed, test results obtained, and any model limitations noted
- Research best practices and stay current of developments in risk management, and share knowledge with business partners and senior management
- Data mining by making sense of large databases of historical data related to credit risk
- Predictive credit risk modelling based on rigorous statistical analyses of historical data, regression techniques, and econometric analyses
- Designs, enhances, and implements a variety of credit models that rely on mathematical, financial, statistical, econometric, machine learning, and artificial intelligence methods
- Bachelor’s degree in relevant field (Finance, Accounting, Economics, or Statistics) and minimum seven to ten years of applicable experience
- Creative problem solver with the ability to improve existing processes and systems using conceptualizing, reasoning, and interpretation skills
- Previous experience building roll rate, vintage, or probabilistic models
- 1+ years of training in and/or experience using Hadoop and related technologies (Spark, Hive)
- Master's degree in Computer Science, Engineering, Finance, Statistics, Mathematics, or related field of study, plus at least 3 years of experience in the role offered, or a computer-related occupation
- MS Excel (intermediate/advanced level Excel incorporating visual basic, and/or Excel macros, ), PowerPoint, Project, and SharePoint
Quantitative Analytics Senior Job Description
- Critically evaluates conceptual soundness of credit models and considers alternate methodologies
- Designs appropriate tests to determine whether models work as designed and monitors existing models for adequate performance
- Work collaboratively with other quantitative analysts with a diverse technical background to share knowledge and implement the most appropriate analytical solution
- Collaborates with credit portfolio managers, Risk Management, Finance, Treasury and lines of businesses to identify opportunities and credit-related risks in the portfolio, making recommendations on new credit origination and risk mitigation strategies
- May supervise or lead the work of other team members
- Oversight of CCR for TDBG
- Oversight of XVA processes for TDS finance, TDGUS including ownership of XVA policy
- Oversight of PB activities in US and Canada and ownership of US PMv2 policy
- Oversight of some aspects of SIMM model (Risk not in SIMM, benchmarking)
- Stress-testing activities related to CCR for TDBG (CCAR, EWST, MST)
- Have a master's degree in economics, IT or engineering
- Have work experience from the banking, energy sector or similar
- Have extensive knowledge of financial products and/or energy markets and experience from working with large sets of data, big data, data mining will be an advantage
- Are motivated by finding simple and robust solutions to complex issues
- Have programming experience, relevant languages may be C++, Python, MatLab, SQL Experience with opensource development stack is an advantage
- Strong experience in valuation of rates and FX options
Quantitative Analytics Senior Job Description
- Support for exposure calculations, CRVA, LEQ
- Market data for CCR
- Quantify and analyze risk exposure characteristics for assigned portfolios / products
- Write detailed technical reports outlining model assumptions, computational methods and results for each project and systematically maintains detailed documentation
- Provide ongoing support for all risk management applications developed
- Raise any issues and/or recommend changes in standards and procedures based on experience
- Demonstrate the ability to manage risk projects independently with minimal supervision
- Build and evolve relationships and interactions with other business units and departments to maximize efficiency
- As directed, provide reporting and other information to external auditors, regulators
- Test policy and methodology used by others to measure risk exposures, including validations statements
- Extensive C++ coding experience
- Experience working closely with options trading desks
- Strong background in machine learning, hypothesis testing, regression analysis, statistics, or probability at the graduate school level or higher, experience creating predictive analytics on noisy data
- Knowledge of quantitative research and the specialized area of financial engineering, data science, or risk analytics as it relates to the securities industry
- Knowledge of financial engineering to analyze risky portfolio covering a wide range of financial instruments, including equities, fixed income, currencies, futures, commodities, and/or derivatives
- Strong background in machine learning, hypothesis testing, regression analysis, statistics, or probability at the graduate school level or higher, experience in creative feature engineering and building predictive analytics on noisy data