Quantitative Risk Analyst Jobs in Connecticut (NOW HIRING)

As a leading financial services and healthcare technology company based on revenue, SS&C is headquartered in Windsor, Connecticut, and has 27,000+ employees in 35 countries. Some 20,000 financial services and healthcare organizations, from the world's largest companies to small and mid-market firms, rely on SS&C for expertise, scale, and technology.
Job Description
Quantitative Financial Engineer (SS&C Technologies, Inc.; Windsor, CT) (Multiple Positions): The Quantitative Financial Engineer is responsible for applying mathematical and statistical techniques to study, measure, and evaluate financial instruments, financial markets and the behavior of market participants. This role typically revolves around the design, development, construction of mathematical models and analytical approaches designed to provide insight into complex financial systems. Specific responsibilities include: Provide support to clients (mainly Hedge Fund Risk Managers) regarding the content and the production of risk reports: answer queries on risk exposures, measures, scenarios, Value-At-Risk calculations and models used within the risk system. Create ad hoc SQL and Python scripts to extract data out of the risk system to facilitate investigations. Work together closely with the risk development team to test and validate new pricing models and enhancements. Reconcile client expectations with the numbers reported by our system using alternate systems such as Bloomberg and/or in house Excel add in libraries. Coordinate and actively participate in the setting up of new clients on the risk platform and configuring the risk engine to conduct the set of analyses as required. Identify and address any ad hoc issues regarding the production of risk reports and escalating to the appropriate team. Provide input and feedback for the continuous enhancement of the system. Telecommuting permitted.
Minimum requirements: Bachelor's degree or equivalent in Mathematics, Applied Science, Business, Finance, Economics or related field plus 2 years of experience in an engineering role. Alternatively, will accept a Master's degree or equivalent in Mathematics, Applied Science, Business, Finance, Economics or related field.
Must have: Knowledge of cross asset class financial instruments modeling and pricing (equity/FX options, bonds, futures, interest-rate swaps, CDS, etc.). Strong understanding of risk management techniques, VaR approaches (Historical, Monte-Carlo) and sensitivity measures (option greeks, DV01, PVO1, etc.). Basic understanding of trading strategies across all major asset classes and hedge fund investment styles. Strong analytic skills and logical reasoning/problem solving. Strong understanding of SQL or Python (Pandas), Excel macros and Bloomberg. Strong understanding of modern programming language and database management concepts. Client-facing experience with excellent written and verbal communication skills.
Apply online at https://www.ssctech.com/about-us/careers or send resume to: Angela Lamar, Talent Acquisition, SS&C Technologies, Inc., alamar@sscinc.com. Ref: 00092349. An EOE.
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Unless explicitly requested or approached by SS&C Technologies, Inc. or any of its affiliated companies, the company will not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services.
SS&C Technologies offers a comprehensive total rewards package designed to support your wellbeing, growth, and future. Our benefits include medical, dental, and vision coverage; a 401(k) plan with company match; paid time off, holidays, and parental leave; and professional development reimbursement opportunity.
Applications will be accepted on an ongoing basis until the position is filled.
SS&C Technologies is an Equal Employment Opportunity employer and does not discriminate against any applicant for employment or employee on the basis of race, color, religious creed, gender, age, marital status, sexual orientation, national origin, disability, veteran status or any other classification protected by applicable discrimination laws.