Principal Embedded Tactical Engineer
1 week ago
Location: Boston, MA
Work Mode: Hybrid (2 days onsite)
About Axelon
Axelon is a leading provider of staffing solutions, dedicated to connecting talented professionals with rewarding opportunities. We pride ourselves on our commitment to excellence and our ability to meet the unique needs of both our clients and candidates.
The Hiring Manager would like to focus only on Privates (Private Equity/Private Credit) experience with candidates in the Boston area.
Description:
- We are seeking a highly skilled and motivated Principal Embedded Tactical Engineer with expertise in Fixed Income, Private Credit, Private Equity, and/or Investment Risk to join our prestigious investment firm.
- As an Embedded Tactical Engineer, you will embed directly within an investment team and work alongside portfolio managers, traders, and other members of the team to develop, implement, and deploy to production small scale applications, proof of concepts, and prototypes that will help improve market analysis, develop investment strategies, and enhance decision-making processes.
- Excellent problem-solving skills, with the ability to think critically, independently, and act with minimal handholding.
- Effective communication skills, with the ability to clearly articulate complex ideas and analysis to both technical and non-technical stakeholders.
- Strong attention to detail, organization, and the ability to manage multiple tasks and priorities in a fast-paced environment.
- Full-stack development knowledge with a minimum of 5 years professional experience programming in Python demonstrating the ability to write efficient and robust code able to process and analyze large financial datasets.
- Experience with key Python Libraries (pandas, NumPy) required. Experience using Version Control (Git) required.
- Strong SQL skills required with a familiarity of financial data platforms (such as Bloomberg, FactSet, Aladdin, eFront), financial databases, and data manipulation techniques preferred.
- Experience with statistical and time-series data analysis using pythonic libraries (such as Scikit-Learn, SciPy, cvxpy) is preferred.
- Practical experience in developing and maintaining models, tools, and reports that showcase a deep understanding of quantitative techniques, methods, statistics and econometrics.
- A solid understanding of financial markets, investment instruments (including Equities, Fixed Income, Derivatives, Private Alternatives), portfolio construction, performance & attribution, and investment strategies.
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