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Data-Intensive Python/SQL Developer with Machine Learning ExperienceThe Cypress Group • New York, New York, United States
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Data-Intensive Python/SQL Developer with Machine Learning Experience

The Cypress Group
  • US
    New York, New York, United States
  • US
    New York, New York, United States
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About

Data-Intensive Python/SQL Developer with Machine Learning Experience Job Title: Quant Developer (Python/SQL) with Machine Learning Transition Location: Lower Manhattan, New York City Employment Type: Full-time Experience Level: 3+ Years Salary: Up to $200k + Bonus About Us: Our client is a leading buy-side firm with a strong commitment to leveraging data-driven insights and machine learning to enhance investment decisions. Located in the heart of Lower Manhattan, we are a dynamic team of professionals dedicated to staying at the forefront of financial technology. Join us in our mission to drive excellence in data analysis and investment strategies. Job Description: Position Overview: We are seeking a talented and motivated Quant Developer with expertise in Python and SQL. This role will initially focus on quantitative development for the first six months, primarily building and optimizing financial data systems, particularly within fixed income. After this period, the role will transition into applying machine learning techniques to enhance data analysis and modeling capabilities. Key Responsibilities:
Develop and maintain Python scripts and applications for data analysis, modeling, and visualization. Build and optimize calculation engines for accounting and financial data, with a focus on fixed income datasets. Collaborate with data engineers to streamline and enhance data pipelines, particularly those handling fixed income securities. Utilize SQL to query and manipulate large datasets, ensuring data accuracy and integrity, with an emphasis on fixed income data structures. Participate in the design and development of data-driven tools and dashboards for investment decision-making. Work closely with portfolio managers and analysts to understand and address their data needs, particularly within fixed income investment strategies. After six months, transition into implementing and optimizing machine learning models for financial data analysis. Stay current with emerging trends and technologies in quantitative finance and machine learning.
Qualifications:
Bachelor's degree in Computer Science, Data Science, Finance, or a related field. Strong programming skills in Python, with experience in data manipulation libraries (e.g., Pandas, NumPy). Proficiency in SQL for querying and managing large datasets. Minimum 3+ years of experience in quantitative development within finance or a related domain. Must have experience in fixed income, ideally loans, but not required. Strong problem-solving skills and attention to detail. Interest and foundational knowledge in machine learning, with the ability and desire to transition into ML work after the initial development phase (experience with Scikit-Learn, TensorFlow, or PyTorch is a plus). Effective communication skills and ability to collaborate in a team-oriented environment. Prior experience in the finance industry is preferred but not required. 5 days a week, onsite in Lower Manhattan. Collaborative and innovative work culture. Competitive salary up to $200,000, with the potential for a performance-based bonus.
How to Apply: If you are a skilled Python/SQL developer eager to start in a quant development role and transition into machine learning, we encourage you to apply by sending your resume and a cover letter detailing your relevant experience to nyjobs@cypressg.com. Our client is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. Note: Unfortunately, visa sponsorship is not available at this time. Seniority level: Associate Employment type: Full-time Job function: Engineering, Finance, and Information Technology Industries: Capital Markets and Financial Services #J-18808-Ljbffr
  • New York, New York, United States

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