Senior Quant Developer

@Aaleen110

I understand you need a Senior Quant Developer to build advanced intra-day trading algorithms for stocks, futures, and crypto, incorporating complex portfolio optimization. My experience developing and deploying high-frequency trading strategies in Python using Pandas and NumPy has consistently delivered a 15% improvement in alpha generation for clients. I will develop your trading algorithms using Python, leveraging Pandas for data manipulation and NumPy for efficient numerical operations. This will include implementing custom risk management modules and building a robust backtesting framework for portfolio optimization, allowing you to simulate strategy performance across different market conditions and asset classes. What is the target latency for these intra-day strategies? Ready to start as soon as you confirm scope.

@vishal1145

Your backtesting framework will produce misleading alpha signals if you're not accounting for slippage and market impact at the tick level. Most intra-day strategies that look profitable in simulation fail in production because they assume infinite liquidity. Quick questions - are you currently using a custom execution simulator or relying on close-to-close fills? And what's your target Sharpe ratio for the live strategies you want to deploy? Here is the architectural approach: - PYTHON SCIENTIFIC STACK: Build vectorized backtesting engine using Pandas/NumPy with microsecond-level timestamp handling to eliminate look-ahead bias in intra-day signals. - PORTFOLIO OPTIMIZATION: Implement mean-variance optimization with transaction cost penalties and position sizing constraints that prevent over-concentration during volatile periods. - RISK MANAGEMENT: Design real-time drawdown monitoring system with circuit breakers that automatically flatten positions when portfolio heat exceeds predefined thresholds. I've built similar intra-day systems for 2 prop trading firms that processed 50K+ trades daily across equities and crypto. Let's schedule a 20-minute technical call to review your current data pipeline and execution latency requirements.

@mdabdullahallm5

With over 8 years of experience in quantitative trading system development and financial software engineering, I can design and implement production-grade algorithmic trading solutions for stocks, futures, and cryptocurrency markets. My expertise includes Python, Pandas, NumPy, VectorBT, Backtrader, QuantConnect LEAN, portfolio optimization, statistical modeling, risk management, and high-performance backtesting frameworks. I have extensive experience building robust trading strategies, developing scalable research and execution infrastructure, integrating market data APIs, and optimizing systems for live trading with strong emphasis on reliability, performance, and clean software architecture. Additionally, I am proficient with PostgreSQL, TimescaleDB, cloud deployment (AWS/GCP), and applying machine learning techniques to financial time-series data. I am confident in delivering maintainable, well-tested, and production-ready quantitative trading solutions while collaborating closely with research and engineering teams to transform trading ideas into profitable, scalable systems.

@alizain721

Intraday strategies fail most often from weak data and execution plumbing, not just model math — without clean, low-latency data and realistic transaction-cost modeling, optimizations look great on paper and blow up live. I’d start by building a reproducible pipeline: tick/quote ingestion with retryable connectors, minute/second resampling, feature factory, then an event-driven signal layer and a vectorized backtester with realistic slippage/fee models. Walk‑forward and cross‑validation plus stress tests (regime shifts) will guard against overfitting. Tech stack: Python (Pandas, NumPy, SciPy), numba for hot loops, cvxpy for convex portfolio optimization (mean‑variance, CVaR, risk‑parity), Backtrader or a lightweight custom engine for intraday, ib_insync/Alpaca/CCXT for execution; Parquet/S3 or ClickHouse for time-series storage; GitLab CI and Docker for deployment. I’ll deliver modular, testable components so strategies, risk rules and execution can be swapped independently. Plan for model versioning, monitoring dashboards, and safe paper-to-live gates. Relevant experience: on Tranero I built robust ETL, API integrations and retry/batch logic for FinTech compliance — the same reliability patterns apply to market data and order routing. Do you have preferred brokers/APIs for live execution and which markets (exchanges) and intraday granularity do you expect to target?

@mobasherreza10

With over 5 years of professional experience and a robust track record in quantitative trading, I'm confident that I have the skills and expertise you need for your Senior Quant Developer role. My solid foundation in statistics, portfolio theory, and risk modeling enables me to design and implement high-performing trading algorithms while mitigating potential risks. Handling data and trading logic for stocks, futures, and cryptocurrency is something I've extensive experience with, ensuring that I can seamlessly dive into the core tasks required by this role. Moreover, I'm a master of Python and well-versed in its scientific stack like Pandas and NumPy as well as experienced with quant frameworks like VectorBT, Backtrader & QuantConnect LEAN. This familiarity is particularly crucial for translating complex quantitative research into production-grade software engineering solutions which aligns perfectly with the bridging role your project seeks.

@Zawiya3

With a solid track record in quantitative or algorithmic trading, I am confident that I can deliver exceptional results as your Senior Quant Developer. I have accumulated over 5 years of professional software engineering experience, and my core competency lies in Python programming with a special knack for its scientific stack—Pandas and NumPy—which are essential for effective financial analysis and modeling. Furthermore, I have hands-on familiarity with advanced backtesting libraries like VectorBT, Backtrader, and QuantConnect LEAN—an invaluable asset for strategizing your trading algorithms. In line with your key responsibilities, I bring to the table a strong foundation in statistics, portfolio theory, risk modeling, and alpha generation – skills that are vital for effective portfolio optimization and risk management. My direct experience handling data and trading logic for stocks, futures, and cryptocurrency sets me apart as a well-rounded professional who can meet your diversified needs.

@dataspro

Nice to meet you , It is a pleasure to communicate with you. My name is Anthony Muñoz, I am the lead engineer for DSPro IT agency and I would like to offer you my professional services. I have more than 10 years of working as a Backend and Software developer, I have successfully completed numerous jobs similar to yours therefore, and after carefully reading the requirements of your project, I consider this job to be suitable to my area of knowledge and skills. I would love to work together to make this project a reality. I greatly appreciate the time provided and I remain pending for any questions or comments. Feel free to contact me. Greetings

@Web1devloper

As a seasoned data analyst and scientist with over 8 years of experience, my proficiency in Python, especially in NumPy and Pandas, provides the solid foundation necessary for your intra-day trading algorithm project. My portfolio includes diverse verticals such as finance, healthcare, e-commerce, and SaaS, enabling me to bring a unique perspective to quantitative finance. I strongly believe in the power of data to tell stories, and I marry this perspective with my backend development skills to not just write codes but build strategies that serve your overall business goals. ​In quant finance, robust backtesting and portfolio optimization are non-negotiables, and these are areas where my forte thrives. Given my dexterity in creating dynamic dashboards (Power BI/Tableau/Looker), I can create comprehensive visualizations of your trading strategies for real-time monitoring and ensure seamless communication with all stakeholders at each step. Lastly, every trading strategy demands timely risk management. Your project explicitly emphasizes this point which resonates well with me as I have always prioritized problem-solving and insights extraction even amidst intricate challenges. With an extensive background in statistical analysis and hypothesis testing, I can confidently vouch for my ability to deliver effective trading algorithms backed by strong risk management protocols. Let's optimize your trading strategies with the precision of analytics!

@swadhinr

I am a Senior Quant Developer with 6+ years of experience building and deploying intraday trading systems across equities and crypto markets. My core expertise lies in Python (Pandas, NumPy) and developing robust backtesting frameworks using tools like VectorBT and custom event-driven engines. In previous roles, I have designed alpha-generating strategies, implemented portfolio optimization models, and built real-time risk systems that monitor exposure, drawdowns, and execution efficiency. I also have hands-on experience integrating market data APIs and execution layers for live trading. I am currently based in Poland/Vietnam and fully aligned with your geographic requirement. I am comfortable working across the full pipeline—from research to production deployment—and ensuring performance, scalability, and reliability. I would be happy to discuss how I can contribute to your trading infrastructure.

@akkiwadhwa1995

I am an AI developer and data scientist with experience delivering production-ready machine learning and AI solutions. I focus on practical, scalable systems that solve real-world problems. Areas of Expertise Machine learning and predictive modeling Computer vision applications Natural language processing systems AI-powered dashboards and automation workflows I ensure transparency in model design, reproducibility of results, and clear documentation for long-term usability. I look forward to discussing how AI can support your project objectives. Regards,

@NEHABHAT92

Drawing on over nine years of experience as a dedicated web and mobile app developer, I am confident in my ability to bring a new perspective to this role as a Senior Quant Developer. My professional journey has allowed me to sharpen my skills in Python, Java, C++, and solidify my grasp on key technologies such as Pandas and NumPy. Additionally, I have thorough experience with high-performance Python tools like Polars and have an intricate understanding of databases such as PostgreSQL and TimescaleDB. Having closely collaborated with programmers from varied disciplines, I've cultivated the essential skill of "bridging gaps", which this job description necessitates. My multi-faceted background in quantitative finance is another significant advantage for this role. Over the years, I have honed a strong foundation in statistics, portfolio theory, risk modelling, and alpha generation directly relevant to your requirements. By choosing me for this pivotal role in your team, you can expect consistent delivery of high-quality work with attention to detail even under pressure. These skills will prove invaluable while designing trading algorithms within your unique workflow system. Additionally, my understanding of cloud infrastructure on platforms such as AWS/GCP aligns well with aligning code scalability and reliable integration useful for bringing clean integration with market data APIs and execution platforms as described in the job description. Will be thrilled to con

@TechizeBuilder

Hi, I’m excited about your project Senior Quant Developer for Intra-Day Trading Algorithms because I specialize in building business management solutions. With expertise in Python, Backend Development, I can develop a complete Inventory Management System featuring stock control, barcode scanning, order management, low-stock alerts, dashboards, and analytics. My focus is on delivering a secure, scalable solution that improves efficiency and supports business growth. Looking forward to working with you.

@codeandcommand

Intra-day algo work is where pipeline speed matters most. I would build the strategy in Python with pandas and NumPy, add a vectorbt backtesting layer to validate signals on historical tick data, and keep signal generation separate from execution logic for easy tuning. Rough timeline is 7 to 10 days. The bid reflects what's in the post. Final scope depends on whether you need live execution wired up or just the backtest layer. Can start today. Want to jump on a quick call?

@loxtic

Hello, how are you doing? I have considerable experience building algo trading systems in Python with Pandas and NumPy, including backtesting and portfolio optimization for intraday strategies across stocks, futures, and crypto. I’ve delivered multiple projects around risk management and algorithmic models that translate well to real-time execution. I can share sample code and approach details if needed. Let me know further information, if interested.

@craigd43

Hi, I have extensive experience developing quantitative trading systems and algorithmic trading solutions across cryptocurrencies, equities, and derivatives. Over the years, I've designed and implemented strategy engines, backtesting frameworks, portfolio and risk management modules, market data integrations, and automated execution systems using Python, Pandas, NumPy, and modern quantitative development practices. My background includes developing high-performance trading infrastructure, optimizing strategies with historical and live market data, integrating exchange and broker APIs, and building scalable systems focused on reliability, execution speed, and maintainability. I also have experience applying machine learning techniques and statistical analysis to improve trading performance and risk control. I'm comfortable working independently in a remote environment and following an iterative development process with clear milestones and regular progress updates. I would welcome the opportunity to discuss your requirements and demonstrate how my experience can contribute to your quantitative trading platform. I look forward to hearing from you.

@iterativeTech

As a seasoned Quant Developer with over five years of experience, I possess the skills and proficiencies you require for your Senior Quant Developer role. My specialization in Python aligns perfectly with your needs, particularly my mastery of Python and proficiency within its scientific stack like Pandas and NumPy - ensuring optimal strategies through robust algorithmic trading. Furthermore, my expertise with quant frameworks like VectorBT, Backtrader, and QuantConnect LEAN equip me well for backtesting and validating your strategies adeptly. Having handled data and trading logic for various asset classes including stocks, futures, and cryptocurrency, I'm well-versed in the dynamics of each type. This competency is vital to your project as it allows me to seamlessly integrate mathematical models for asset allocation, risk management, and portfolio rebalancing. In addition, my experience with high-performance Python tools like Polars and my knowledge of machine learning workflows applied to financial data complement the cutting-edge work that your organisation carries out. Optimal infrastructural integretion is a top priority to ensure code scalability, reliability, along with neat connection to market data APIs -- something that I have been deeply involved in throughout my career through the deployment of cloud infrastructure like AWS/GCP.

@jagratip3

I can support you as a Senior Quant Developer to design, implement, and optimize algorithmic trading strategies across equities, futures, and crypto with a strong focus on intraday execution, risk control, and portfolio-level performance. I have strong experience in Python-based quantitative systems using Pandas, NumPy, and SciPy for data processing, signal generation, and strategy research. My background includes building end-to-end trading pipelines—from data ingestion and feature engineering to backtesting, optimization, and performance evaluation. For your project, I would focus on: • Robust strategy development with statistically validated signals • Portfolio optimization using risk-adjusted frameworks (Sharpe, Sortino, drawdown control) • Backtesting engine design with realistic slippage, fees, and latency assumptions • Risk management layers including position sizing, exposure limits, and volatility scaling • Modular architecture so strategies can be easily extended across assets (stocks, futures, crypto) I can collaborate on both strategy research and full implementation, including live-trading integration if required. I’d be happy to discuss your current dataset, infrastructure, and preferred execution venue so I can align the system design with your trading objectives.

@erincguray

Greetings, I am Erinc. I am a Full stack developer knowledgeable in Python and Data Processing. I can help you with Quant Development. Looking forward to hear from you. Thanks for your consideration.

@arturg6

Hello, intra‑day trading algorithms – you need a robust, high‑performing solution that can handle stocks, futures and crypto while staying within tight latency budgets. I’ll build the backtesting pipeline with VectorBT on Polars DataFrames, pre‑loading market data into memory and using lazy evaluation so the UI stays under 200 ms on cold load. For portfolio optimization I’ll apply a mean‑variance solver with exposure and turnover constraints, and a risk module that flags drawdowns in real‑time, while also handling missing bars from exchange outages. Which broker API are you targeting for live execution? Looking forward to working with you. Artur Giżycki