Fixed-Income Data Engineer

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Fixed-Income Data Engineer – Austin, TX

 

Amherst is revolutionizing the way U.S. real estate is priced, managed and financed in order to unlock opportunities for all market participants. Driven by data, analytics and technology, Amherst has a 20-year history of anticipating where the next risks and opportunities are likely to emerge and designing actionable strategies for investors to capitalize on opportunities across residential real estate, commercial real estate and public securities. Amherst, along with its affiliates and subsidiaries, has more than 1,000 employees, $5 billion under management and approximately $15 billion under advisement and oversight. In 2019, Bungalo sold its 250th home, and Amherst managed 25,000th home. To learn more, please visit www.amherst.com. 

 

We are looking for a Fixed-Income Data Engineer who is self-motivated, output-oriented individual with strong technical skills who is driven by intellectual curiosity to understand the complexities of financial markets and has experience with the Agency MBS market. The individual will have opportunities to be part of high-level meetings with senior members of the investment teams and have a direct impact on the company's strategy and success. 

 

Responsibilities:

  • Work collaboratively on projects and analyses utilizing specialized quantitative skills to generate value-added insights and provide data-driven solutions to enhance investment outcomes for the Agency MBS desk.
  • Drive and use relational-based database technologies and Big Data platforms to research new and innovative techniques and methods to solve problems in support of investment decision making for fixed income.
  • Support deep analysis of investment strategies, create new quantitative measures, and contribute to new investment strategies.
  • Develop business acumen to bring an informed perspective to investment management teams.
  • Use communication and interpersonal skills to integrate with the portfolio management teams. Tailor communication of complex concepts to the audience.
  • Participate in special projects and perform other duties as assigned.

Qualifications

  • Graduate degree in a quantitative/analytical field such as Financial Engineering or Computer Science.
  • Minimum of 3–5 years of experience as a Fixed Income desk quant or equivalent combination of education/training.
  • Knowledge of capital markets and investment concepts. Knowledge of Agency MBS preferred.
  • Excellent interpersonal and communication skills.
  • Strong proficiency in computer programming, such as Python, C#, C++, C, R, and Big Data related technologies.
  • Strong proficiency in SQL related technologies, such as Microsoft SQL Server, Oracle, MySQL, Hive, Presto, etc.
  • Ability to work independently and in a team environment.
  • Demonstrates a high degree of motivation.
  • BONUS: Intex modeling/data experience

What We Offer:

 

Amherst’s WeWork office is located on Barton Springs Rd. near the heart of downtown Austin and within walking distance of Lady Bird Lake.

  • A competitive compensation package, annual bonus, 401k match
  • Flexible PTO, 8 paid holidays
  • Employer-paid benefits (medical, dental, vision, health savings account)
  • Stellar colleagues with proven track records 
  • Parking pass provided (parking located in the Palmer Events Center across the street)
  • Free sodas, kombucha, cold brew, and snacks
  • Monthly lunch stipends and breakfast tacos on Thursdays!
  • Monthly/Weekly office events!

Amherst is proud to be an Equal Opportunity Employer and committed to creating an inclusive environment for all employees. We do not discriminate on the basis of race, color, religion, national origin, gender, pregnancy, sexual orientation, gender identity, age, physical or mental disability, genetic information or veteran status, and encourage all applicants to apply.

 

 

 

 

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Location

Austin at our HQ with beautiful views of Lake Austin in a modern office as well as our second office in the top floor of the Frost Tower downtown

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