Mid-level Quantitative Developer

New Jersey, United States

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Not SpecifiedCompensation

Mid-level (3 to 4 years)Experience Level

Full TimeJob Type

UnknownVisa

Financial Services, BiotechnologyIndustries

Requirements

Candidates should possess a Bachelor's degree or higher in computer science or a related technical area, along with 4-5 years of experience in programming for a professional setting. Proficiency in the Python programming language and its scientific computing ecosystem (numpy, Pandas, Arrow, etc.) is preferred, and familiarity with the state-of-the-art data engineering ecosystem is a plus. Experience in processing financial data and machine learning is also beneficial, as is knowledge of quantitative research and trading.

Responsibilities

The Mid-level Quantitative Developer will design, develop, maintain, and optimize in-house research data platforms, providing quantitative researchers with reliable data sources and analysis tools. They will establish protocols for data injection, processing, quality assurance, and anomaly detection, and streamline processes. The role also involves working with external partners to onboard new datasets, conducting data analysis, and collaborating with quant researchers to evaluate new data sources. Furthermore, the developer will develop and maintain quantitative research tools, demonstrating fast, rigorous, and critical thinking skills while effectively communicating and thriving in a fast-paced team environment.

Skills

Python

numpy

Pandas

Arrow

Data Engineering

Financial Data Processing

Machine Learning

Quantitative Research

Trading

Data Analysis

Data Mining

Programming

Data Platforms

Data Quality Assurance

Anomaly Detection

Archiving

Tower Research Capital

High-frequency trading and technology solutions

About Tower Research Capital

Tower Research Capital operates in the financial markets by providing high-frequency trading services. The company uses advanced technology and algorithms to execute trades at very high speeds, allowing it to take advantage of small price discrepancies in the market. Its main clients are institutional investors, hedge funds, and other financial entities that need fast and reliable trading solutions. Tower Research Capital's business model focuses on generating profits through proprietary trading strategies and executing a large volume of trades with minimal delay. The company continually invests in research and development to stay ahead of its competitors in the high-frequency trading industry.

New York City, New YorkHeadquarters

1998Year Founded

$60MTotal Funding

VENTURE_UNKNOWNCompany Stage

Quantitative Finance, Financial ServicesIndustries

1,001-5,000Employees

Benefits

5 weeks of paid vacation per year

401(k) with company matching

Free meals and snacks

Reimbursement for health and wellness expenses

Risks

Talent drain to competitors may impact Tower's competitive edge in high-frequency trading.

Increased competition from new trading platforms could challenge Tower's market share.

Diversification into ventures like Sporttrade might divert focus from core trading activities.

Differentiation

Tower Research Capital excels in high-frequency trading with advanced algorithms and technology.

The firm offers rapid and reliable trading solutions for institutional investors and hedge funds.

Tower Research Capital continuously invests in R&D to maintain its competitive edge.

Upsides

Increased focus on AI-driven trading strategies enhances Tower's algorithmic capabilities.

Tower's investment in blockchain technology improves transaction speed and security.

Collaboration with academic institutions boosts algorithm development and innovation.

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